diff --git a/PAMI/fuzzyFrequentPattern/basic/FFIMiner.py b/PAMI/fuzzyFrequentPattern/basic/FFIMiner.py index 37cca92d..f8961b22 100644 --- a/PAMI/fuzzyFrequentPattern/basic/FFIMiner.py +++ b/PAMI/fuzzyFrequentPattern/basic/FFIMiner.py @@ -1,13 +1,14 @@ -# Fuzzy Frequent Pattern-Miner is desired to find all frequent fuzzy patterns which is on-trivial and challenging problem -# -# to its huge search space.we are using efficient pruning techniques to reduce the search space. +# Fuzzy Frequent Pattern-Miner is desired to find all frequent fuzzy patterns which is on-trivial and challenging problem to its huge search space.we are using efficient pruning techniques to reduce the search space. # # **Importing this algorithm into a python program** -# --------------------------------------------------------- # # from PAMI.fuzzyFrequentPattern import FFIMiner as alg # -# obj = alg.FFIMiner("input.txt", 2) +# iFile = 'sampleTDB.txt' +# +# minSup = 0.25 # can be specified between 0 and 1 +# +# obj = alg.FFIMiner(iFile, minSup, sep) # # obj.mine() # @@ -56,119 +57,73 @@ class FFIMiner(_ab._fuzzyFrequentPattenrs): """ - :Description: Fuzzy Frequent Pattern-Miner is desired to find all frequent fuzzy patterns which is on-trivial and challenging problem - to its huge search space.we are using efficient pruning techniques to reduce the search space. - - :Reference: Lin, Chun-Wei & Li, Ting & Fournier Viger, Philippe & Hong, Tzung-Pei. (2015). - A fast Algorithm for mining fuzzy frequent itemsets. Journal of Intelligent & Fuzzy Systems. 29. - 2373-2379. 10.3233/IFS-151936. - https://www.researchgate.net/publication/286510908_A_fast_Algorithm_for_mining_fuzzy_frequent_itemSets - - :param iFile: str : - Name of the Input file to mine complete set of frequent patterns - :param oFile: str : - Name of the output file to store complete set of frequent patterns - :param minSup: int or float or str : - The user can specify minSup either in count or proportion of database size. If the program detects the data type of minSup is integer, then it treats minSup is expressed in count. Otherwise, it will be treated as float. - :param maxPer: float : - The user can specify maxPer in count or proportion of database size. If the program detects the data type of maxPer is integer, then it treats maxPer is expressed in count. - :param fuzFile: str : - The user can specify fuzFile. - :param sep: str : - This variable is used to distinguish items from one another in a transaction. The default seperator is tab space. However, the users can override their default separator. - - - :Attributes: - - iFile : string - Name of the input file to mine complete set of fuzzy frequent patterns - - fmFile : string - Name of the fuzzy membership file to mine complete set of fuzzy frequent patterns - - oFile : string - Name of the oFile file to store complete set of fuzzy frequent patterns - - minSup : float - The user given minimum support - - memoryRSS : float - To store the total amount of RSS memory consumed by the program - - startTime:float - To record the start time of the mining process - - endTime:float - To record the completion time of the mining process - - itemsCnt: int - To record the number of fuzzy spatial itemSets generated - - mapItemSum: map - To keep track of sum of Fuzzy Values of items - - joinsCnt: int - To keep track of the number of ffi-list that was constructed - - BufferSize: int - represent the size of Buffer - - itemSetBuffer list - to keep track of items in buffer - - :Methods: - - mine() - Mining process will start from here - getPatterns() - Complete set of patterns will be retrieved with this function - save(oFile) - Complete set of frequent patterns will be loaded in to a output file - getPatternsAsDataFrame() - Complete set of frequent patterns will be loaded in to a dataframe - getMemoryUSS() - Total amount of USS memory consumed by the mining process will be retrieved from this function - getMemoryRSS() - Total amount of RSS memory consumed by the mining process will be retrieved from this function - getRuntime() - Total amount of runtime taken by the mining process will be retrieved from this function - convert(value) - To convert the given user specified value - compareItems(o1, o2) - A Function that sort all ffi-list in ascending order of Support - FSFIMining(prefix, prefixLen, FSFIM, minSup) - Method generate ffi from prefix - construct(px, py) - A function to construct Fuzzy itemSet from 2 fuzzy itemSets - findElementWithTID(uList, tid) - To find element with same tid as given - WriteOut(prefix, prefixLen, item, sumIUtil) - To Store the patten - - - **Executing the code on terminal :** - ------------------------------------------ + **About this algorithm** + + :**Description**: Fuzzy Frequent Pattern-Miner is desired to find all frequent fuzzy patterns which is on-trivial and challenging problem + to its huge search space.we are using efficient pruning techniques to reduce the search space. + + :**Reference**: Lin, Chun-Wei & Li, Ting & Fournier Viger, Philippe & Hong, Tzung-Pei. (2015). + A fast Algorithm for mining fuzzy frequent itemsets. Journal of Intelligent & Fuzzy Systems. 29. + 2373-2379. 10.3233/IFS-151936. + https://www.researchgate.net/publication/286510908_A_fast_Algorithm_for_mining_fuzzy_frequent_itemSets + + :**parameters**: - **iFile** (*str*) -- *Name of the Input file to mine complete set of correlated patterns* + - **oFile** (*str*) -- *Name of the output file to store complete set of correlated patterns* + - **minSup** (*int or float or str*) -- *The user can specify minSup either in count or proportion of database size. If the program detects the data type of minSup is integer, then it treats minSup is expressed in count.* + - **sep** (*str*) -- *This variable is used to distinguish items from one another in a transaction. The default seperator is tab space. However, the users can override their default separator.* + + :**Attributes**: - **memoryUSS** (*float*) -- *To store the total amount of USS memory consumed by the program.* + - **memoryRSS** (*float*) -- *To store the total amount of RSS memory consumed by the program.* + - **startTime** (*float*) -- *To record the start time of the mining process.* + - **endTime** (*float*) -- *To record the completion time of the mining process.* + - **itemsCnt** (*int*) -- *To record the number of fuzzy spatial itemSets generated.* + - **mapItemSum** (*int*) -- *To keep track of sum of Fuzzy Values of items.* + - **joinsCnt** (*int*) -- * To keep track of the number of ffi-list that was constructed.* + - **BufferSize** (*int*) -- *Represent the size of Buffer.* + - **itemSetBuffer** (*list*) -- *To keep track of items in buffer.* + + :**Methods**: - **mine()** -- *Mining process will start from here.* + - **getPatterns()** -- *Complete set of patterns will be retrieved with this function.* + - **save(oFile)** -- *Complete set of frequent patterns will be loaded in to a output file.* + - **getPatternsAsDataFrame()** -- *Complete set of frequent patterns will be loaded in to a dataframe.* + - **getMemoryUSS()** -- *Total amount of USS memory consumed by the mining process will be retrieved from this function.* + - **getMemoryRSS()** -- *Total amount of RSS memory consumed by the mining process will be retrieved from this function.* + - **getRuntime()** -- *Total amount of runtime taken by the mining process will be retrieved from this function.* + - **convert(value)** -- *To convert the given user specified value.* + - **compareItems(o1, o2)** -- *A Function that sort all ffi-list in ascending order of Support.* + - **FSFIMining(prefix, prefixLen, FSFIM, minSup)** -- *Method generate ffi from prefix.* + - **construct(px, py)** -- *A function to construct Fuzzy itemSet from 2 fuzzy itemSets.* + - **findElementWithTID(uList, tid)** -- *To find element with same tid as given.* + - **WriteOut(prefix, prefixLen, item, sumIUtil)** -- *To Store the pattern.* + + **Execution methods** + + **Terminal command** .. code-block:: console Format: - (.venv) $ python3 FFIMiner.py + (.venv) $ python3 FFIMiner.py Example Usage: (.venv) $ python3 FFIMiner.py sampleTDB.txt output.txt 6 - .. note:: minSup will be considered in percentage of database transactions + .. note:: minSup can be specified in support count or a value between 0 and 1. + + **Calling from a python program** - **Sample run of importing the code:** - ------------------------------------------ .. code-block:: python from PAMI.fuzzyFrequentPattern import FFIMiner as alg - obj = alg.FFIMiner("input.txt", 2) + iFile = 'sampleTDB.txt' + + minSup = 0.25 # can be specified between 0 and 1 + + obj = alg.CoMine(iFile, minSup, sep) obj.mine() @@ -191,9 +146,9 @@ class FFIMiner(_ab._fuzzyFrequentPattenrs): print("Total ExecutionTime in seconds:", run) - **Credits:** - --------------- - The complete program was written by B.Sai Chitra under the supervision of Professor Rage Uday Kiran. + **Credits** + + The complete program was written by B.Sai Chitra and revised by Tarun Sreepada under the supervision of Professor Rage Uday Kiran. """ @@ -289,6 +244,20 @@ def _convert(self, value) -> Union[int, float]: return value def dfs(self, cands): + """ + Perform depth-first search (DFS) to find frequent patterns in a database. + + This method recursively combines candidate patterns and calculates their support + in the database, storing frequent patterns and their support counts. + + :param cands: List of candidate patterns represented as tuples. + :type cands: list + :return: None + + This method does not return anything explicitly, but it updates internal + attributes `_finalPatterns` and `_Database` with frequent patterns and their + support counts. + """ for i in range(len(cands)): newCands = [] for j in range(i + 1, len(cands)): @@ -307,6 +276,9 @@ def dfs(self, cands): self.dfs(newCands) def mine(self): + """ + Main() function start from here. + """ self._startTime = _ab._time.time() items = {} lineNo = 0 diff --git a/finalSphinxDocs/_build/doctrees/PAMI.fuzzyFrequentPattern.basic.doctree b/finalSphinxDocs/_build/doctrees/PAMI.fuzzyFrequentPattern.basic.doctree index 3f1076b6..adf48cb0 100644 Binary files a/finalSphinxDocs/_build/doctrees/PAMI.fuzzyFrequentPattern.basic.doctree and b/finalSphinxDocs/_build/doctrees/PAMI.fuzzyFrequentPattern.basic.doctree differ diff --git a/finalSphinxDocs/_build/doctrees/environment.pickle b/finalSphinxDocs/_build/doctrees/environment.pickle index a0f5c878..f3d51114 100644 Binary files a/finalSphinxDocs/_build/doctrees/environment.pickle and b/finalSphinxDocs/_build/doctrees/environment.pickle differ diff --git a/finalSphinxDocs/_build/doctrees/fuzzyFrequentPatternbasicFFIMiner.doctree b/finalSphinxDocs/_build/doctrees/fuzzyFrequentPatternbasicFFIMiner.doctree index 42ed0f3e..4b02ecd9 100644 Binary files a/finalSphinxDocs/_build/doctrees/fuzzyFrequentPatternbasicFFIMiner.doctree and b/finalSphinxDocs/_build/doctrees/fuzzyFrequentPatternbasicFFIMiner.doctree differ diff --git a/finalSphinxDocs/_build/html/PAMI.fuzzyFrequentPattern.basic.html b/finalSphinxDocs/_build/html/PAMI.fuzzyFrequentPattern.basic.html index b790edf5..1bd1f2be 100644 --- a/finalSphinxDocs/_build/html/PAMI.fuzzyFrequentPattern.basic.html +++ b/finalSphinxDocs/_build/html/PAMI.fuzzyFrequentPattern.basic.html @@ -105,6 +105,7 @@

Submodules class PAMI.fuzzyFrequentPattern.basic.FFIMiner.FFIMiner(iFile: str, minSup: float, sep: str = '\t')[source]

Bases: _fuzzyFrequentPattenrs

+

About this algorithm

Description:

Fuzzy Frequent Pattern-Miner is desired to find all frequent fuzzy patterns which is on-trivial and challenging problem @@ -118,82 +119,48 @@

SubmodulesParameters:
    -

  • iFile – str : -Name of the Input file to mine complete set of frequent patterns

    • -

  • oFile – str : -Name of the output file to store complete set of frequent patterns

    • -

  • minSup – int or float or str : -The user can specify minSup either in count or proportion of database size. If the program detects the data type of minSup is integer, then it treats minSup is expressed in count. Otherwise, it will be treated as float.

    • -

  • maxPer – float : -The user can specify maxPer in count or proportion of database size. If the program detects the data type of maxPer is integer, then it treats maxPer is expressed in count.

    • -

  • fuzFile – str : -The user can specify fuzFile.

    • -

  • sep – str : -This variable is used to distinguish items from one another in a transaction. The default seperator is tab space. However, the users can override their default separator.

    • +

  • iFile (str) – Name of the Input file to mine complete set of correlated patterns

    • +

  • oFile (str) – Name of the output file to store complete set of correlated patterns

    • +

  • minSup (int or float or str) – The user can specify minSup either in count or proportion of database size. If the program detects the data type of minSup is integer, then it treats minSup is expressed in count.

    • +

  • sep (str) – This variable is used to distinguish items from one another in a transaction. The default seperator is tab space. However, the users can override their default separator.

Attributes:
-
-
iFilestring

Name of the input file to mine complete set of fuzzy frequent patterns

-
-
fmFilestring

Name of the fuzzy membership file to mine complete set of fuzzy frequent patterns

-
-
oFilestring

Name of the oFile file to store complete set of fuzzy frequent patterns

-
-
minSupfloat

The user given minimum support

-
-
memoryRSSfloat

To store the total amount of RSS memory consumed by the program

-
-
startTime:float

To record the start time of the mining process

-
-
endTime:float

To record the completion time of the mining process

-
-
itemsCnt: int

To record the number of fuzzy spatial itemSets generated

-
-
mapItemSum: map

To keep track of sum of Fuzzy Values of items

-
-
joinsCnt: int

To keep track of the number of ffi-list that was constructed

-
-
BufferSize: int

represent the size of Buffer

-
-
itemSetBuffer list

to keep track of items in buffer

-
-
+
    +

  • memoryUSS (float) – To store the total amount of USS memory consumed by the program.

    • +

  • memoryRSS (float) – To store the total amount of RSS memory consumed by the program.

    • +

  • startTime (float) – To record the start time of the mining process.

    • +

  • endTime (float) – To record the completion time of the mining process.

    • +

  • itemsCnt (int) – To record the number of fuzzy spatial itemSets generated.

    • +

  • mapItemSum (int) – To keep track of sum of Fuzzy Values of items.

    • +

  • joinsCnt (int) – * To keep track of the number of ffi-list that was constructed.*

    • +

  • BufferSize (int) – Represent the size of Buffer.

    • +

  • itemSetBuffer (list) – To keep track of items in buffer.

    • +
Methods:
-
-
mine()

Mining process will start from here

-
-
getPatterns()

Complete set of patterns will be retrieved with this function

-
-
save(oFile)

Complete set of frequent patterns will be loaded in to a output file

-
-
getPatternsAsDataFrame()

Complete set of frequent patterns will be loaded in to a dataframe

-
-
getMemoryUSS()

Total amount of USS memory consumed by the mining process will be retrieved from this function

-
-
getMemoryRSS()

Total amount of RSS memory consumed by the mining process will be retrieved from this function

-
-
getRuntime()

Total amount of runtime taken by the mining process will be retrieved from this function

-
-
convert(value)

To convert the given user specified value

-
-
compareItems(o1, o2)

A Function that sort all ffi-list in ascending order of Support

-
-
FSFIMining(prefix, prefixLen, FSFIM, minSup)

Method generate ffi from prefix

-
-
construct(px, py)

A function to construct Fuzzy itemSet from 2 fuzzy itemSets

-
-
findElementWithTID(uList, tid)

To find element with same tid as given

-
-
WriteOut(prefix, prefixLen, item, sumIUtil)

To Store the patten

-
-
+
    +

  • mine() – Mining process will start from here.

    • +

  • getPatterns() – Complete set of patterns will be retrieved with this function.

    • +

  • save(oFile) – Complete set of frequent patterns will be loaded in to a output file.

    • +

  • getPatternsAsDataFrame() – Complete set of frequent patterns will be loaded in to a dataframe.

    • +

  • getMemoryUSS() – Total amount of USS memory consumed by the mining process will be retrieved from this function.

    • +

  • getMemoryRSS() – Total amount of RSS memory consumed by the mining process will be retrieved from this function.

    • +

  • getRuntime() – Total amount of runtime taken by the mining process will be retrieved from this function.

    • +

  • convert(value) – To convert the given user specified value.

    • +

  • compareItems(o1, o2) – A Function that sort all ffi-list in ascending order of Support.

    • +

  • FSFIMining(prefix, prefixLen, FSFIM, minSup) – Method generate ffi from prefix.

    • +

  • construct(px, py) – A function to construct Fuzzy itemSet from 2 fuzzy itemSets.

    • +

  • findElementWithTID(uList, tid) – To find element with same tid as given.

    • +

  • WriteOut(prefix, prefixLen, item, sumIUtil) – To Store the pattern.

    • +

+

Execution methods

+

Terminal command

Format:
 
-(.venv) $ python3 FFIMiner.py <inputFile> <outputFile> <minSup> <separator>
+(.venv) $ python3 FFIMiner.py <inputFile> <outputFile> <minSup> <sep>
 
 Example Usage:
 
@@ -202,11 +169,16 @@ 
Submodules
 
Note

-
minSup will be considered in percentage of database transactions

+
minSup can be specified in support count or a value between 0 and 1.
+

Calling from a python program

from PAMI.fuzzyFrequentPattern import FFIMiner as alg
 
-obj = alg.FFIMiner("input.txt", 2)
+iFile = 'sampleTDB.txt'
+
+minSup = 0.25 # can be specified between 0 and 1
+
+obj = alg.CoMine(iFile, minSup, sep)
 
 obj.mine()
 
@@ -229,9 +201,27 @@ 
Submodulesprint("Total ExecutionTime in seconds:", run)
-
-

The complete program was written by B.Sai Chitra under the supervision of Professor Rage Uday Kiran.

-
+

Credits

+

The complete program was written by B.Sai Chitra and revised by Tarun Sreepada under the supervision of Professor Rage Uday Kiran.

+
+
+dfs(cands)[source]
+

Perform depth-first search (DFS) to find frequent patterns in a database.

+

This method recursively combines candidate patterns and calculates their support +in the database, storing frequent patterns and their support counts.

+
+
Parameters:
+

cands (list) – List of candidate patterns represented as tuples.

+
+
Returns:
+

None

+
+
+

This method does not return anything explicitly, but it updates internal +attributes _finalPatterns and _Database with frequent patterns and their +support counts.

+
+
getMemoryRSS() → float[source]
@@ -304,8 +294,8 @@

Submodules
-mine() → None[source]
-

fuzzy-Frequent pattern mining process will start from here

+mine()[source] +

Main() function start from here.

@@ -333,8 +323,8 @@

Submodules
-startMine() → None[source]
-

fuzzy-Frequent pattern mining process will start from here

+startMine()[source] +

Code for the mining process will start from this function

diff --git a/finalSphinxDocs/_build/html/_modules/PAMI/fuzzyFrequentPattern/basic/FFIMiner.html b/finalSphinxDocs/_build/html/_modules/PAMI/fuzzyFrequentPattern/basic/FFIMiner.html index a461bb6c..9329b544 100644 --- a/finalSphinxDocs/_build/html/_modules/PAMI/fuzzyFrequentPattern/basic/FFIMiner.html +++ b/finalSphinxDocs/_build/html/_modules/PAMI/fuzzyFrequentPattern/basic/FFIMiner.html @@ -94,16 +94,17 @@

Source code for PAMI.fuzzyFrequentPattern.basic.FFIMiner

-# Fuzzy Frequent  Pattern-Miner is desired to find all  frequent fuzzy patterns which is on-trivial and challenging problem
-#
-# to its huge search space.we are using efficient pruning techniques to reduce the search space.
+# Fuzzy Frequent  Pattern-Miner is desired to find all  frequent fuzzy patterns which is on-trivial and challenging problem to its huge search space.we are using efficient pruning techniques to reduce the search space.
 #
 # **Importing this algorithm into a python program**
-# ---------------------------------------------------------
 #
 #             from PAMI.fuzzyFrequentPattern import FFIMiner as alg
 #
-#             obj = alg.FFIMiner("input.txt", 2)
+#             iFile = 'sampleTDB.txt'
+#
+#             minSup = 0.25 # can be specified between 0 and 1
+#
+#             obj = alg.FFIMiner(iFile, minSup, sep)
 #
 #             obj.mine()
 #
@@ -127,8 +128,6 @@ 
Source code for PAMI.fuzzyFrequentPattern.basic.FFIMiner
#
 
 
-
-
 __copyright__ = """
 Copyright (C)  2021 Rage Uday Kiran
 
@@ -152,207 +151,75 @@ 
Source code for PAMI.fuzzyFrequentPattern.basic.FFIMiner
from typing import List, Dict, Tuple, Set, Union, Any, Generator
 from deprecated import deprecated
 
-
-class _FFList:
-    """
-    A class represent a Fuzzy List of an element
-
-    :Attributes:
-
-        item: int
-            the item name
-
-        sumIUtil: float
-            the sum of utilities of a fuzzy item in database
-
-        sumRUtil: float
-            the sum of resting values of a fuzzy item in database
-
-        elements: list
-            a list of elements contain tid,Utility and resting values of element in each transaction
-
-    :Methods:
-
-        addElement(element)
-            Method to add an element to this fuzzy list and update the sums at the same time.
-
-        printElement(e)
-            Method to print elements
-    """
-
-    def __init__(self, itemName: int) -> None:
-        self.item = itemName
-        self.sumIUtil = 0.0
-        self.sumRUtil = 0.0
-        self.elements = []
-
-    def addElement(self, element) -> None:
-        """
-        A Method that add a new element to FFList
-
-        :param element: an element to be added to FFList
-        :type element: Element
-        :return: None
-        """
-        self.sumIUtil += element.iUtils
-        self.sumRUtil += element.rUtils
-        self.elements.append(element)
-
-    def printElement(self) -> None:
-        """
-        A method to print elements
-        """
-        for ele in self.elements:
-            print(ele.tid, ele.iUtils, ele.rUtils)
-
-
-class _Element:
-    """
-    A class represents an Element of a fuzzy list
-
-    :Attributes:
-
-        tid : int
-            keep tact of transaction id
-
-        iUtils: float
-            the utility of a fuzzy item in the transaction
-
-        rUtils : float
-            the  resting value of a fuzzy item in the transaction
-    """
-
-    def __init__(self, tid: int, iUtil: float, rUtil: float) -> None:
-        self.tid = tid
-        self.iUtils = iUtil
-        self.rUtils = rUtil
-
-
-class _Pair:
-    """
-    A class to store item and it's quantity together
-    """
-
-    def __init__(self) -> None:
-        self.item = 0
-        self.quantity = 0
-
-
 
[docs]class FFIMiner(_ab._fuzzyFrequentPattenrs):
     """
-    :Description:   Fuzzy Frequent  Pattern-Miner is desired to find all  frequent fuzzy patterns which is on-trivial and challenging problem
-                    to its huge search space.we are using efficient pruning techniques to reduce the search space.
-
-    :Reference:   Lin, Chun-Wei & Li, Ting & Fournier Viger, Philippe & Hong, Tzung-Pei. (2015).
-                  A fast Algorithm for mining fuzzy frequent itemsets. Journal of Intelligent & Fuzzy Systems. 29.
-                  2373-2379. 10.3233/IFS-151936.
-                  https://www.researchgate.net/publication/286510908_A_fast_Algorithm_for_mining_fuzzy_frequent_itemSets
-
-    :param  iFile: str :
-                   Name of the Input file to mine complete set of frequent patterns
-    :param  oFile: str :
-                   Name of the output file to store complete set of frequent patterns
-    :param  minSup: int or float or str :
-                   The user can specify minSup either in count or proportion of database size. If the program detects the data type of minSup is integer, then it treats minSup is expressed in count. Otherwise, it will be treated as float.
-    :param maxPer: float :
-                   The user can specify maxPer in count or proportion of database size. If the program detects the data type of maxPer is integer, then it treats maxPer is expressed in count.
-    :param fuzFile: str :
-                    The user can specify fuzFile.
-    :param  sep: str :
-                   This variable is used to distinguish items from one another in a transaction. The default seperator is tab space. However, the users can override their default separator.
-
-
-    :Attributes:
-
-        iFile : string
-            Name of the input file to mine complete set of fuzzy  frequent patterns
-
-        fmFile : string
-            Name of the fuzzy membership file to mine complete set of fuzzy  frequent patterns
-
-        oFile : string
-            Name of the oFile file to store complete set of fuzzy  frequent patterns
-
-        minSup : float
-            The user given minimum support
-
-        memoryRSS : float
-            To store the total amount of RSS memory consumed by the program
-
-        startTime:float
-            To record the start time of the mining process
-
-        endTime:float
-            To record the completion time of the mining process
-
-        itemsCnt: int
-            To record the number of fuzzy spatial itemSets generated
-
-        mapItemSum: map
-            To keep track of sum of Fuzzy Values of items
-
-        joinsCnt: int
-            To keep track of the number of ffi-list that was constructed
-
-        BufferSize: int
-            represent the size of Buffer
-
-        itemSetBuffer list
-            to keep track of items in buffer
-
-    :Methods:
-
-        mine()
-            Mining process will start from here
-        getPatterns()
-            Complete set of patterns will be retrieved with this function
-        save(oFile)
-            Complete set of frequent patterns will be loaded in to a output file
-        getPatternsAsDataFrame()
-            Complete set of frequent patterns will be loaded in to a dataframe
-        getMemoryUSS()
-            Total amount of USS memory consumed by the mining process will be retrieved from this function
-        getMemoryRSS()
-            Total amount of RSS memory consumed by the mining process will be retrieved from this function
-        getRuntime()
-            Total amount of runtime taken by the mining process will be retrieved from this function
-        convert(value)
-            To convert the given user specified value
-        compareItems(o1, o2)
-            A Function that sort all ffi-list in ascending order of Support
-        FSFIMining(prefix, prefixLen, FSFIM, minSup)
-            Method generate ffi from prefix
-        construct(px, py)
-            A function to construct Fuzzy itemSet from 2 fuzzy itemSets
-        findElementWithTID(uList, tid)
-            To find element with same tid as given
-        WriteOut(prefix, prefixLen, item, sumIUtil)
-            To Store the patten
-
-
-    **Executing the code on terminal :**
-    ------------------------------------------
+    **About this algorithm**
+
+    :**Description**:   Fuzzy Frequent  Pattern-Miner is desired to find all  frequent fuzzy patterns which is on-trivial and challenging problem
+                        to its huge search space.we are using efficient pruning techniques to reduce the search space.
+
+    :**Reference**:   Lin, Chun-Wei & Li, Ting & Fournier Viger, Philippe & Hong, Tzung-Pei. (2015).
+                      A fast Algorithm for mining fuzzy frequent itemsets. Journal of Intelligent & Fuzzy Systems. 29.
+                      2373-2379. 10.3233/IFS-151936.
+                      https://www.researchgate.net/publication/286510908_A_fast_Algorithm_for_mining_fuzzy_frequent_itemSets
+
+    :**parameters**:    - **iFile** (*str*) -- *Name of the Input file to mine complete set of correlated patterns*
+                        - **oFile** (*str*) -- *Name of the output file to store complete set of correlated patterns*
+                        - **minSup** (*int or float or str*) -- *The user can specify minSup either in count or proportion of database size. If the program detects the data type of minSup is integer, then it treats minSup is expressed in count.*
+                        - **sep** (*str*) -- *This variable is used to distinguish items from one another in a transaction. The default seperator is tab space. However, the users can override their default separator.*
+
+    :**Attributes**:   - **memoryUSS** (*float*) -- *To store the total amount of USS memory consumed by the program.*
+                        - **memoryRSS** (*float*) -- *To store the total amount of RSS memory consumed by the program.*
+                        - **startTime** (*float*) -- *To record the start time of the mining process.*
+                        - **endTime** (*float*) -- *To record the completion time of the mining process.*
+                        - **itemsCnt** (*int*) -- *To record the number of fuzzy spatial itemSets generated.*
+                        - **mapItemSum** (*int*) -- *To keep track of sum of Fuzzy Values of items.*
+                        - **joinsCnt** (*int*) -- * To keep track of the number of ffi-list that was constructed.*
+                        - **BufferSize** (*int*) -- *Represent the size of Buffer.*
+                        - **itemSetBuffer** (*list*) -- *To keep track of items in buffer.*
+
+    :**Methods**:    - **mine()** -- *Mining process will start from here.*
+                     - **getPatterns()** -- *Complete set of patterns will be retrieved with this function.*
+                     - **save(oFile)** -- *Complete set of frequent patterns will be loaded in to a output file.*
+                     - **getPatternsAsDataFrame()** -- *Complete set of frequent patterns will be loaded in to a dataframe.*
+                     - **getMemoryUSS()** -- *Total amount of USS memory consumed by the mining process will be retrieved from this function.*
+                     - **getMemoryRSS()** -- *Total amount of RSS memory consumed by the mining process will be retrieved from this function.*
+                     - **getRuntime()** -- *Total amount of runtime taken by the mining process will be retrieved from this function.*
+                     - **convert(value)** -- *To convert the given user specified value.*
+                     - **compareItems(o1, o2)** -- *A Function that sort all ffi-list in ascending order of Support.*
+                     - **FSFIMining(prefix, prefixLen, FSFIM, minSup)** -- *Method generate ffi from prefix.*
+                     - **construct(px, py)** -- *A function to construct Fuzzy itemSet from 2 fuzzy itemSets.*
+                     - **findElementWithTID(uList, tid)** -- *To find element with same tid as given.*
+                     - **WriteOut(prefix, prefixLen, item, sumIUtil)** -- *To Store the pattern.*
+
+    **Execution methods**
+
+    **Terminal command**
 
     .. code-block:: console
 
       Format:
 
-      (.venv) $ python3 FFIMiner.py <inputFile> <outputFile> <minSup> <separator>
+      (.venv) $ python3 FFIMiner.py <inputFile> <outputFile> <minSup> <sep>
 
       Example Usage:
 
       (.venv) $ python3  FFIMiner.py sampleTDB.txt output.txt 6
 
-    .. note:: minSup will be considered in percentage of database transactions
+    .. note:: minSup can be specified in support count or a value between 0 and 1.
 
 
-    **Sample run of importing the code:**
-    ------------------------------------------
+    **Calling from a python program**
+
     .. code-block:: python
 
             from PAMI.fuzzyFrequentPattern import FFIMiner as alg
 
-            obj = alg.FFIMiner("input.txt", 2)
+            iFile = 'sampleTDB.txt'
+
+            minSup = 0.25 # can be specified between 0 and 1
+
+            obj = alg.CoMine(iFile, minSup, sep)
 
             obj.mine()
 
@@ -375,9 +242,9 @@ 
Source code for PAMI.fuzzyFrequentPattern.basic.FFIMiner
            print("Total ExecutionTime in seconds:", run)
 
 
-    **Credits:**
-    ---------------
-            The complete program was written by B.Sai Chitra under the supervision of Professor Rage Uday Kiran.
+    **Credits**
+
+    The complete program was written by B.Sai Chitra and revised by Tarun Sreepada under the supervision of Professor Rage Uday Kiran.
 
     """
 
@@ -397,58 +264,13 @@ 
Source code for PAMI.fuzzyFrequentPattern.basic.FFIMiner
super().__init__(iFile, minSup, sep)
         self._startTime = 0
         self._endTime = 0
-        self._itemsCnt = 0
-        self._mapItemSum = {}
-        self._joinsCnt = 0
-        self._BufferSize = 200
-        self._itemSetBuffer = []
-        self._transactions = []
-        self._fuzzyValues = []
-        self._finalPatterns = {}
         self._dbLen = 0
-
-    def _compareItems(self, o1: _FFList, o2: _FFList) -> int:
-        """
-        A Function that sort all ffi-list in ascending order of Support
-
-        :param o1: First FFI-list
-        :type o1: _FFList
-        :param o2: Second FFI-list
-        :type o1: _FFList
-        :return: Comparision Value
-        :rtype: int
-        """
-        compare = self._mapItemSum[o1.item] - self._mapItemSum[o2.item]
-        if compare == 0:
-            if o1.item < o2.item:
-                return -1
-            elif o1.item > o2.item:
-                return 1
-            else:
-                return 0
-        else:
-            return compare
-
-    def _convert(self, value) -> Union[int, float]:
-        """
-        To convert the given user specified value
-
-        :param value: user specified value
-        :type value: int or float or str
-        :return: converted value
-        :rtype: int or float
-        """
-        if type(value) is int:
-            value = int(value)
-        if type(value) is float:
-            value = (self._dbLen * value)
-        if type(value) is str:
-            if '.' in value:
-                value = float(value)
-                value = (self._dbLen * value)
-            else:
-                value = int(value)
-        return value
+        self._minSup = minSup
+        self._iFile = iFile
+        self._sep = sep
+        self._finalPatterns = {}
+        self._memoryUSS = 0
+        self._memoryRSS = 0
 
     def _creatingItemsets(self) -> None:
         """
@@ -492,67 +314,94 @@ 
Source code for PAMI.fuzzyFrequentPattern.basic.FFIMiner
except IOError:
                     print("File Not Found")
                     quit()
+    
+
[docs]    def startMine(self):
+        self.mine()

 
-
[docs]    @deprecated("It is recommended to use 'mine()' instead of 'startMine()' for mining process. Starting from January 2025, 'startMine()' will be completely terminated.")
-    def startMine(self) -> None:
+    def _convert(self, value) -> Union[int, float]:
         """
-        fuzzy-Frequent pattern mining process will start from here
+        To convert the given user specified value
+
+        :param value: user specified value
+        :type value: int or float or str
+        :return: converted value
+        :rtype: int or float
         """
-        self.mine()

+        if type(value) is int:
+            value = int(value)
+        if type(value) is float:
+            value = (self._dbLen * value)
+        if type(value) is str:
+            if '.' in value:
+                value = float(value)
+                value = (self._dbLen * value)
+            else:
+                value = int(value)
+        return value
+    
+
[docs]    def dfs(self, cands):
+        """
+        Perform depth-first search (DFS) to find frequent patterns in a database.
+
+        This method recursively combines candidate patterns and calculates their support
+        in the database, storing frequent patterns and their support counts.
 
-
[docs]    def mine(self) -> None:
+        :param cands: List of candidate patterns represented as tuples.
+        :type cands: list
+        :return: None
+
+        This method does not return anything explicitly, but it updates internal
+        attributes `_finalPatterns` and `_Database` with frequent patterns and their
+        support counts.
+        """
+        for i in range(len(cands)):
+            newCands = []
+            for j in range(i + 1, len(cands)):
+                newCand = tuple(cands[i] + tuple([cands[j][-1]]))
+                # print(items[cands[i]], items[cands[j]])
+                newCandItems = {}
+                keys = self._Database[cands[i]].keys() & self._Database[cands[j]].keys()
+                for k in keys:
+                    newCandItems[k] = min(self._Database[cands[i]][k], self._Database[cands[j]][k])
+                count = sum(newCandItems.values())
+                if count >= self._minSup:
+                    newCands.append(newCand)
+                    self._finalPatterns[newCand] = count
+                    self._Database[newCand] = newCandItems
+            if len(newCands) > 1:
+                self.dfs(newCands)

+
+
[docs]    def mine(self):
         """
-        fuzzy-Frequent pattern mining process will start from here
+        Main() function start from here.
         """
         self._startTime = _ab._time.time()
+        items = {}
+        lineNo = 0
         self._creatingItemsets()
-        for line in range(len(self._transactions)):
-            items = self._transactions[line]
-            quantities = self._fuzzyValues[line]
-            self._dbLen += 1
-            for i in range(0, len(items)):
-                item = items[i]
-                if item in self._mapItemSum:
-                    self._mapItemSum[item] += quantities[i]
-                else:
-                    self._mapItemSum[item] = quantities[i]
-        listOfffilist = []
-        mapItemsToFFLIST = {}
-        #self._minSup = self._convert(self._minSup)
-        # minSup = self.minSup
-        for item1 in self._mapItemSum.keys():
-            item = item1
-            if self._mapItemSum[item] >= self._minSup:
-                fuList = _FFList(item)
-                mapItemsToFFLIST[item] = fuList
-                listOfffilist.append(fuList)
-        listOfffilist.sort(key=_ab._functools.cmp_to_key(self._compareItems))
-        tid = 0
-        for line in range(len(self._transactions)):
-            items = self._transactions[line]
-            quantities = self._fuzzyValues[line]
-            revisedTransaction = []
-            for i in range(0, len(items)):
-                pair = _Pair()
-                pair.item = items[i]
-                pair.quantity = quantities[i]
-                item = pair.item
-                if self._mapItemSum[item] >= self._minSup:
-                    if pair.quantity > 0:
-                        revisedTransaction.append(pair)
-            revisedTransaction.sort(key=_ab._functools.cmp_to_key(self._compareItems))
-            for i in range(len(revisedTransaction) - 1, -1, -1):
-                pair = revisedTransaction[i]
-                remainUtil = 0
-                for j in range(len(revisedTransaction) - 1, i, -1):
-                    remainUtil += revisedTransaction[j].quantity
-                remainingUtility = remainUtil
-                if mapItemsToFFLIST.get(pair.item) is not None:
-                    FFListOfItem = mapItemsToFFLIST[pair.item]
-                    element = _Element(tid, pair.quantity, remainingUtility)
-                    FFListOfItem.addElement(element)
-            tid += 1
-        self._FFIMining(self._itemSetBuffer, 0, listOfffilist, self._minSup)
+
+        self._dbLen = len(self._transactions)
+        for transactions, fuzzyValues in zip(self._transactions, self._fuzzyValues):
+            for item, fuzzyValue in zip(transactions, fuzzyValues):
+                item = tuple([item])
+                if item not in items:
+                    items[item] = {}
+                items[item][lineNo] = fuzzyValue
+            lineNo += 1
+
+        self._minSup = self._convert(self._minSup)
+        self._Database = items.copy()
+
+        supports = {k:sum(v.values()) for k,v in items.items()}
+        supports = {k:v for k,v in supports.items() if v >= self._minSup}
+        self._Database = {k:v for k,v in items.items() if k in supports}
+        self._Database = {k:v for k,v in sorted(self._Database.items(), key=lambda x: sum(x[1].values()), reverse=True)}
+
+        self._finalPatterns = supports.copy()
+
+        cands = list(self._Database.keys())
+        self.dfs(cands)
+
         self._endTime = _ab._time.time()
         process = _ab._psutil.Process(_ab._os.getpid())
         self._memoryUSS = float()
@@ -560,31 +409,32 @@ 
Source code for PAMI.fuzzyFrequentPattern.basic.FFIMiner
self._memoryUSS = process.memory_full_info().uss
         self._memoryRSS = process.memory_info().rss

 
-    def _FFIMining(self, prefix, prefixLen, FSFIM, minSup):
+
+
[docs]    def getPatternsAsDataFrame(self) -> _ab._pd.DataFrame:
         """
-        Generates ffi from prefix
-
-        :param prefix: the prefix patterns of ffi
-        :type prefix: len
-        :param prefixLen: the length of prefix
-        :type prefixLen: int
-        :param FSFIM: the Fuzzy list of prefix itemSets
-        :type FSFIM: list
-        :param minSup: the minimum support of
-        :type minSup: int or float
+        Storing final frequent patterns in a dataframe
+
+        :return: returning frequent patterns in a dataframe
+        :rtype: pd.DataFrame
         """
-        for i in range(0, len(FSFIM)):
-            X = FSFIM[i]
-            if X.sumIUtil >= minSup:
-                self._WriteOut(prefix, prefixLen, X.item, X.sumIUtil)
-            if X.sumRUtil >= minSup:
-                exULs = []
-                for j in range(i + 1, len(FSFIM)):
-                    Y = FSFIM[j]
-                    exULs.append(self._construct(X, Y))
-                    self._joinsCnt += 1
-                self._itemSetBuffer.insert(prefixLen, X.item)
-                self._FFIMining(self._itemSetBuffer, prefixLen + 1, exULs, minSup)
+
+        # dataFrame = {}
+        # data = []
+        # for a, b in self._finalPatterns.items():
+        #     data.append([a.replace('\t', ' '), b])
+        #     dataFrame = _ab._pd.DataFrame(data, columns=['Patterns', 'Support'])
+        # dataFrame = _fp._pd.DataFrame(list([[" ".join(x), y] for x,y in self._finalPatterns.items()]), columns=['Patterns', 'Support'])
+        dataFrame = _ab._pd.DataFrame(list([[" ".join(x), y] for x, y in self._finalPatterns.items()]), columns=['Patterns', 'Support'])
+        return dataFrame

+
+
[docs]    def getPatterns(self) -> dict:
+        """
+        Function to send the set of frequent patterns after completion of the mining process
+
+        :return: returning frequent patterns
+        :rtype: dict
+        """
+        return self._finalPatterns

 
 
[docs]    def getMemoryUSS(self) -> float:
         """
@@ -614,96 +464,6 @@ 
Source code for PAMI.fuzzyFrequentPattern.basic.FFIMiner
        """
         return self._endTime - self._startTime

 
-    def _construct(self, px, py) -> _FFList:
-        """
-        A function to construct a new Fuzzy itemSet from 2 fuzzy itemSets
-
-        :param px:the itemSet px
-        :type px:ffi-List
-        :param py:itemSet py
-        :type py:ffi-List
-        :return :the itemSet of pxy(px and py)
-        :rtype :ffi-List
-        """
-        pxyUL = _FFList(py.item)
-        for ex in px.elements:
-            ey = self._findElementWithTID(py, ex.tid)
-            if ey is None:
-                continue
-            eXY = _Element(ex.tid, min([ex.iUtils, ey.iUtils], key=lambda x: float(x)), ey.rUtils)
-            pxyUL.addElement(eXY)
-        return pxyUL
-
-    def _findElementWithTID(self, uList, tid) -> _Element:
-        """
-        To find element with same tid as given
-
-        :param uList: fuzzyList
-        :type uList: ffi-List
-        :param tid: transaction id
-        :type tid: int
-        :return: element  tid as given
-        :rtype: element if exit or None
-        """
-        List = uList.elements
-        first = 0
-        last = len(List) - 1
-        while first <= last:
-            mid = (first + last) >> 1
-            if List[mid].tid < tid:
-                first = mid + 1
-            elif List[mid].tid > tid:
-                last = mid - 1
-            else:
-                return List[mid]
-        return None
-
-    def _WriteOut(self, prefix: list, prefixLen: int, item: int, sumIUtil: float) -> None:
-        """
-        To Store the patten
-
-        :param prefix: prefix of itemSet
-        :type prefix: list
-        :param prefixLen: length of prefix
-        :type prefixLen: int
-        :param item: the last item
-        :type item: int
-        :param sumIUtil: sum of utility of itemSet
-        :type sumIUtil: float
-        :return: None
-        """
-        self._itemsCnt += 1
-        res = ""
-        for i in range(0, prefixLen):
-            res += str(prefix[i])  + "\t"
-        res += str(item)
-        res1 = str(sumIUtil)
-        self._finalPatterns[res] = res1
-
-
[docs]    def getPatternsAsDataFrame(self) -> _ab._pd.DataFrame:
-        """
-        Storing final frequent patterns in a dataframe
-
-        :return: returning frequent patterns in a dataframe
-        :rtype: pd.DataFrame
-        """
-
-        dataFrame = {}
-        data = []
-        for a, b in self._finalPatterns.items():
-            data.append([a.replace('\t', ' '), b])
-            dataFrame = _ab._pd.DataFrame(data, columns=['Patterns', 'Support'])
-        return dataFrame

-
-
[docs]    def getPatterns(self) -> dict:
-        """
-        Function to send the set of frequent patterns after completion of the mining process
-
-        :return: returning frequent patterns
-        :rtype: dict
-        """
-        return self._finalPatterns

-
 
[docs]    def save(self, outFile) -> dict:
         """
         Complete set of frequent patterns will be loaded in to an output file
@@ -713,11 +473,15 @@ 
Source code for PAMI.fuzzyFrequentPattern.basic.FFIMiner
        :return: dictionary of frequent patterns
         :rtype: dict
         """
-        self._oFile = outFile
-        writer = open(self._oFile, 'w+')
-        for x, y in self._finalPatterns.items():
-            patternsAndSupport = x.strip() + ":" + str(y)
-            writer.write("%s \n" % patternsAndSupport)

+        # self._oFile = outFile
+        # writer = open(self._oFile, 'w+')
+        # for x, y in self._finalPatterns.items():
+        #     patternsAndSupport = x.strip() + ":" + str(y)
+        #     writer.write("%s \n" % patternsAndSupport)
+        with open(outFile, 'w') as f:
+            for x, y in self._finalPatterns.items():
+                x = "\t".join(x)
+                f.write(f"{x}:{y}\n")

 
 
[docs]    def printResults(self) -> None:
         """
@@ -744,11 +508,12 @@ 
Source code for PAMI.fuzzyFrequentPattern.basic.FFIMiner
print("Total Memory in RSS", _ap.getMemoryRSS())
         print("Total ExecutionTime in seconds:", _ap.getRuntime())
     else:
-        _ap = FFIMiner('sample.txt', 1, ' ')
-        _ap.startMine()
+        _ap = FFIMiner('/Users/tarunsreepada/Downloads/Fuzzy_T10I4D100K.csv', 400, '\t')
+        # _ap.startMine()
         _ap.mine()
         print("Total number of Fuzzy-Frequent Patterns:", len(_ap.getPatterns()))
         _ap.save('output.txt')
+        print(_ap.getPatternsAsDataFrame())
         print("Total Memory in USS:", _ap.getMemoryUSS())
         print("Total Memory in RSS", _ap.getMemoryRSS())
         print("Total ExecutionTime in seconds:", _ap.getRuntime())
diff --git a/finalSphinxDocs/_build/html/fuzzyFrequentPatternbasicFFIMiner.html b/finalSphinxDocs/_build/html/fuzzyFrequentPatternbasicFFIMiner.html
index 41b9a3e2..d284e0a1 100644
--- a/finalSphinxDocs/_build/html/fuzzyFrequentPatternbasicFFIMiner.html
+++ b/finalSphinxDocs/_build/html/fuzzyFrequentPatternbasicFFIMiner.html
@@ -118,6 +118,7 @@
 

 class PAMI.fuzzyFrequentPattern.basic.FFIMiner.FFIMiner(iFile: str, minSup: float, sep: str = '\t')[source]

 
Bases: _fuzzyFrequentPattenrs

+
About this algorithm

 

 
Description:

 
Fuzzy Frequent  Pattern-Miner is desired to find all  frequent fuzzy patterns which is on-trivial and challenging problem
@@ -131,82 +132,48 @@
 

 
Parameters:

 
    
-
  • iFile – str :
-Name of the Input file to mine complete set of frequent patterns
    • 
-
  • oFile – str :
-Name of the output file to store complete set of frequent patterns
    • 
-
  • minSup – int or float or str :
-The user can specify minSup either in count or proportion of database size. If the program detects the data type of minSup is integer, then it treats minSup is expressed in count. Otherwise, it will be treated as float.
    • 
-
  • maxPer – float :
-The user can specify maxPer in count or proportion of database size. If the program detects the data type of maxPer is integer, then it treats maxPer is expressed in count.
    • 
-
  • fuzFile – str :
-The user can specify fuzFile.
    • 
-
  • sep – str :
-This variable is used to distinguish items from one another in a transaction. The default seperator is tab space. However, the users can override their default separator.
    • 
+
  • iFile (str) – Name of the Input file to mine complete set of correlated patterns
    • 
+
  • oFile (str) – Name of the output file to store complete set of correlated patterns
    • 
+
  • minSup (int or float or str) – The user can specify minSup either in count or proportion of database size. If the program detects the data type of minSup is integer, then it treats minSup is expressed in count.
    • 
+
  • sep (str) – This variable is used to distinguish items from one another in a transaction. The default seperator is tab space. However, the users can override their default separator.
    • 
 

 

 
Attributes:

-

-
iFilestring
Name of the input file to mine complete set of fuzzy  frequent patterns

-

-
fmFilestring
Name of the fuzzy membership file to mine complete set of fuzzy  frequent patterns

-

-
oFilestring
Name of the oFile file to store complete set of fuzzy  frequent patterns

-

-
minSupfloat
The user given minimum support

-

-
memoryRSSfloat
To store the total amount of RSS memory consumed by the program

-

-
startTime:float
To record the start time of the mining process

-

-
endTime:float
To record the completion time of the mining process

-

-
itemsCnt: int
To record the number of fuzzy spatial itemSets generated

-

-
mapItemSum: map
To keep track of sum of Fuzzy Values of items

-

-
joinsCnt: int
To keep track of the number of ffi-list that was constructed

-

-
BufferSize: int
represent the size of Buffer

-

-
itemSetBuffer list
to keep track of items in buffer

-

-

+
    
+
  • memoryUSS (float) – To store the total amount of USS memory consumed by the program.
    • 
+
  • memoryRSS (float) – To store the total amount of RSS memory consumed by the program.
    • 
+
  • startTime (float) – To record the start time of the mining process.
    • 
+
  • endTime (float) – To record the completion time of the mining process.
    • 
+
  • itemsCnt (int) – To record the number of fuzzy spatial itemSets generated.
    • 
+
  • mapItemSum (int) – To keep track of sum of Fuzzy Values of items.
    • 
+
  • joinsCnt (int) – * To keep track of the number of ffi-list that was constructed.*
    • 
+
  • BufferSize (int) – Represent the size of Buffer.
    • 
+
  • itemSetBuffer (list) – To keep track of items in buffer.
    • 
+

 

 
Methods:

-

-
mine()
Mining process will start from here

-

-
getPatterns()
Complete set of patterns will be retrieved with this function

-

-
save(oFile)
Complete set of frequent patterns will be loaded in to a output file

-

-
getPatternsAsDataFrame()
Complete set of frequent patterns will be loaded in to a dataframe

-

-
getMemoryUSS()
Total amount of USS memory consumed by the mining process will be retrieved from this function

-

-
getMemoryRSS()
Total amount of RSS memory consumed by the mining process will be retrieved from this function

-

-
getRuntime()
Total amount of runtime taken by the mining process will be retrieved from this function

-

-
convert(value)
To convert the given user specified value

-

-
compareItems(o1, o2)
A Function that sort all ffi-list in ascending order of Support

-

-
FSFIMining(prefix, prefixLen, FSFIM, minSup)
Method generate ffi from prefix

-

-
construct(px, py)
A function to construct Fuzzy itemSet from 2 fuzzy itemSets

-

-
findElementWithTID(uList, tid)
To find element with same tid as given

-

-
WriteOut(prefix, prefixLen, item, sumIUtil)
To Store the patten

-

-

+
    
+
  • mine() – Mining process will start from here.
    • 
+
  • getPatterns() – Complete set of patterns will be retrieved with this function.
    • 
+
  • save(oFile) – Complete set of frequent patterns will be loaded in to a output file.
    • 
+
  • getPatternsAsDataFrame() – Complete set of frequent patterns will be loaded in to a dataframe.
    • 
+
  • getMemoryUSS() – Total amount of USS memory consumed by the mining process will be retrieved from this function.
    • 
+
  • getMemoryRSS() – Total amount of RSS memory consumed by the mining process will be retrieved from this function.
    • 
+
  • getRuntime() – Total amount of runtime taken by the mining process will be retrieved from this function.
    • 
+
  • convert(value) – To convert the given user specified value.
    • 
+
  • compareItems(o1, o2) – A Function that sort all ffi-list in ascending order of Support.
    • 
+
  • FSFIMining(prefix, prefixLen, FSFIM, minSup) – Method generate ffi from prefix.
    • 
+
  • construct(px, py) – A function to construct Fuzzy itemSet from 2 fuzzy itemSets.
    • 
+
  • findElementWithTID(uList, tid) – To find element with same tid as given.
    • 
+
  • WriteOut(prefix, prefixLen, item, sumIUtil) – To Store the pattern.
    • 
+

 

 

+
Execution methods

+
Terminal command

 
Format:
 
-(.venv) $ python3 FFIMiner.py <inputFile> <outputFile> <minSup> <separator>
+(.venv) $ python3 FFIMiner.py <inputFile> <outputFile> <minSup> <sep>
 
 Example Usage:
 
@@ -215,11 +182,16 @@
 

 

 
Note

-
minSup will be considered in percentage of database transactions

+
minSup can be specified in support count or a value between 0 and 1.

 

+
Calling from a python program

 
from PAMI.fuzzyFrequentPattern import FFIMiner as alg
 
-obj = alg.FFIMiner("input.txt", 2)
+iFile = 'sampleTDB.txt'
+
+minSup = 0.25 # can be specified between 0 and 1
+
+obj = alg.CoMine(iFile, minSup, sep)
 
 obj.mine()
 
@@ -242,9 +214,27 @@
 print("Total ExecutionTime in seconds:", run)
 

 

-

-
The complete program was written by B.Sai Chitra under the supervision of Professor Rage Uday Kiran.

-

+
Credits

+
The complete program was written by B.Sai Chitra and revised by Tarun Sreepada under the supervision of Professor Rage Uday Kiran.

+

+

+dfs(cands)[source]

+
Perform depth-first search (DFS) to find frequent patterns in a database.

+
This method recursively combines candidate patterns and calculates their support
+in the database, storing frequent patterns and their support counts.

+

+
Parameters:

+
cands (list) – List of candidate patterns represented as tuples.

+

+
Returns:

+
None

+

+

+
This method does not return anything explicitly, but it updates internal
+attributes _finalPatterns and _Database with frequent patterns and their
+support counts.

+

+
 

 

 getMemoryRSS() → float[source]

@@ -317,8 +307,8 @@
 
 

 

-mine() → None[source]

-
fuzzy-Frequent pattern mining process will start from here

+mine()[source]
+
Main() function start from here.

 

 
 

@@ -346,8 +336,8 @@
 
 

 

-startMine() → None[source]

-
fuzzy-Frequent pattern mining process will start from here

+startMine()[source]
+
Code for the mining process will start from this function

 

 
 

diff --git a/finalSphinxDocs/_build/html/genindex.html b/finalSphinxDocs/_build/html/genindex.html
index 03461b77..7c39d39c 100644
--- a/finalSphinxDocs/_build/html/genindex.html
+++ b/finalSphinxDocs/_build/html/genindex.html
@@ -408,10 +408,12 @@ 
D

 
       
       
  • DenseFormatDFPlus (class in PAMI.extras.DF2DB.denseDF2DBPlus)
+
    • 
+      
  • DF2Fig (class in PAMI.extras.graph.DF2Fig)
 
    • 
   
   
      
-      
    • DF2Fig (class in PAMI.extras.graph.DF2Fig)
+      
    • dfs() (PAMI.fuzzyFrequentPattern.basic.FFIMiner.FFIMiner method), [1]
 
      • 
       
    • DFSCode (class in PAMI.subgraphMining.basic.dfsCode)
 
      • 
diff --git a/finalSphinxDocs/_build/html/objects.inv b/finalSphinxDocs/_build/html/objects.inv
index 0d0cfaed..7ff26c76 100644
Binary files a/finalSphinxDocs/_build/html/objects.inv and b/finalSphinxDocs/_build/html/objects.inv differ
diff --git a/finalSphinxDocs/_build/html/searchindex.js b/finalSphinxDocs/_build/html/searchindex.js
index 81fff1ed..d14a5acb 100644
--- a/finalSphinxDocs/_build/html/searchindex.js
+++ b/finalSphinxDocs/_build/html/searchindex.js
@@ -1 +1 @@
-Search.setIndex({"docnames": ["ContiguousFrequentPatterns1", "CorrelatedPatternMining1", "CoveragePatternMining1", "FaultTolerantPatternMining1", "FrequentPatternWithMultipleMinimumSupport1", "FuzzyCorrelatedPatternMining1", "FuzzyFrequentPatternMining1", "FuzzyGeoReferencedFrequentPatternMining1", "FuzzyGeoReferencedPeriodicFrequentPatternMining1", "FuzzyPeriodicFrequentPatternMining1", "GeoReferencedFrequentPatternMining1", "GeoReferencedFrequentSequencePatternMining1", "GeoReferencedPartialPeriodicPatternMining1", "GeoReferencedPeriodicFrequentPatternMining1", "HighUtilityFrequentPatternMining1", "HighUtilityGeo-referencedFrequentPatternMining1", "HighUtilityPatternMining1", "HighUtilitySpatialPatternMining1", "LocalPeriodicPatternMining1", "MultiplePartialPeriodicPatternMining1", "PAMI", "PAMI.AssociationRules", "PAMI.AssociationRules.basic", "PAMI.correlatedPattern", "PAMI.correlatedPattern.basic", "PAMI.coveragePattern", "PAMI.coveragePattern.basic", "PAMI.extras", 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"PAMI.localPeriodicPattern.basic", "PAMI.multipleMinimumSupportBasedFrequentPattern", "PAMI.multipleMinimumSupportBasedFrequentPattern.basic", "PAMI.partialPeriodicFrequentPattern", "PAMI.partialPeriodicFrequentPattern.basic", "PAMI.partialPeriodicPattern", "PAMI.partialPeriodicPattern.basic", "PAMI.partialPeriodicPattern.closed", "PAMI.partialPeriodicPattern.maximal", "PAMI.partialPeriodicPattern.pyspark", "PAMI.partialPeriodicPattern.topk", "PAMI.partialPeriodicPatternInMultipleTimeSeries", "PAMI.periodicCorrelatedPattern", "PAMI.periodicCorrelatedPattern.basic", "PAMI.periodicFrequentPattern", "PAMI.periodicFrequentPattern.basic", "PAMI.periodicFrequentPattern.closed", "PAMI.periodicFrequentPattern.cuda", "PAMI.periodicFrequentPattern.maximal", "PAMI.periodicFrequentPattern.pyspark", "PAMI.periodicFrequentPattern.topk", "PAMI.periodicFrequentPattern.topk.TopkPFP", "PAMI.periodicFrequentPattern.topk.kPFPMiner", "PAMI.recurringPattern", "PAMI.recurringPattern.basic", 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"PAMI.weightedFrequentRegularPattern.basic", "PAMI.weightedUncertainFrequentPattern", "PAMI.weightedUncertainFrequentPattern.basic", "PartialPeriodicFrequentPatternMining1", "PartialPeriodicPatternMining1", "PeriodicCorrelatedPatternMining1", "PeriodicFrequentPatternMining1", "RecurringPatternMining1", "RelativeHighUtilityPatternMining1", "SequentialFrequentPatternMining1", "StablePeriodicPatternMining1", "UncertainFrequentPatternMining1", "UncertainGeoReferencedFrequentPatternMining1", "UncertainPeriodicFrequentPatternMining1", "WeightedFrequentNeighbourhoodPatternMining1", "WeightedFrequentPatternMining1", "WeightedFrequentRegularPatternMining1", "contiguousFrequentPatterns", "contiguousPatternMining", "correlatedPatternBasicCoMine", "correlatedPatternBasicCoMinePlus", "correlatedPatternMining", "coveragePatternBasicCMine", "coveragePatternBasicCPPG", "coveragePatternMining", "faultTolerantFrequentPatternBasicFTApriori", "faultTolerantFrequentPatternBasicFTFPGrowth", 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"geoReferencedFrequentSequencePatternMining.rst", "geoReferencedPartialPeriodicPatternMining.rst", "geoReferencedPatternMining.rst", "geoReferencedPeriodicFrequentPatternMining.rst", "geoReferencedPeriodicFrequentPatternbasicGPFPMiner.rst", "georeferencedFrequentPatternbasicFSPGrowth.rst", "georeferencedFrequentPatternbasicSpatialECLAT.rst", "georeferencedPartialPeriodicPatternbasicSTEclat.rst", "highUtilityFrequentPatternBasicHUFIM.rst", "highUtilityFrequentPatternMining.rst", "highUtilityGeo-referencedFrequentPatternMining.rst", "highUtilityGeoreferencedFrequentPatternBasicSHUFIM.rst", "highUtilityPatternBasicEFIM.rst", "highUtilityPatternBasicHMiner.rst", "highUtilityPatternBasicUPGrowth.rst", "highUtilityPatternMining.rst", "highUtilitySpatialPatternBasicHDSHUIM.rst", "highUtilitySpatialPatternBasicSHUIM.rst", "highUtilitySpatialPatternMining.rst", "highUtilitySpatialPatternTopkTKSHUIM.rst", "index.rst", "localPeriodicPatternMining.rst", "localPeriodicPatternbasicLPPGrowth.rst", "localPeriodicPatternbasicLPPMBreadth.rst", "localPeriodicPatternbasicLPPMDepth.rst", "modules.rst", "multipleMinimumSupportBasedFrequentPatternBasicCFPGrowth.rst", "multipleMinimumSupportBasedFrequentPatternBasicCFPGrowthPlus.rst", "multiplePartialPeriodicPatternMining.rst", "multipleTimeseriesPatternMining.rst", "partialPeriodicFrequentPatternMining.rst", "partialPeriodicFrequentPatternbasicGPFgrowth.rst", "partialPeriodicFrequentPatternbasicPPF_DFS.rst", "partialPeriodicPatternInMultipleTimeSeriesPPGrowth.rst", "partialPeriodicPatternMining.rst", "partialPeriodicPatternbasicGThreePGrowth.rst", "partialPeriodicPatternbasicPPPGrowth.rst", "partialPeriodicPatternbasicPPP_ECLAT.rst", "partialPeriodicPatternclosedPPPClose.rst", "partialPeriodicPatternmaximalMax3PGrowth.rst", "partialPeriodicPatterntopkk3PMiner.rst", "periodicCorrelatedPatternMining.rst", "periodicCorrelatedPatternbasicEPCPGrowth.rst", "periodicFrequentPatternMining.rst", "periodicFrequentPatternbasicPFECLAT.rst", "periodicFrequentPatternbasicPFPGrowth.rst", "periodicFrequentPatternbasicPFPGrowthPlus.rst", "periodicFrequentPatternbasicPFPMC.rst", "periodicFrequentPatternbasicPSGrowth.rst", "periodicFrequentPatternclosedCPFPMiner.rst", "periodicFrequentPatternmaximalMaxPFGrowth.rst", "periodicFrequentPatterntopkTopkPFPTopkPFP.rst", "periodicFrequentPatterntopkkPFPMinerkPFPMiner.rst", "recurringPatternMining.rst", "recurringPatternbasicRPGrowth.rst", "relativeFrequent.rst", "relativeFrequentPattern.rst", "relativeFrequentPatternBasicRSFPGrowth.rst", "relativeHighUtilityPatternBasicRHUIM.rst", "relativeHighUtilityPatternMining.rst", "sequentialFrequentPatternMining.rst", "sequentialPatternMining.rst", "sequentialPatternMiningBasicSPADE.rst", "sequentialPatternMiningBasicSPAM.rst", "sequentialPatternMiningBasicprefixSpan.rst", "sequentialPatternMiningClosedbide.rst", "stablePeriodicFrequentPatternbasicSPPEclat.rst", "stablePeriodicFrequentPatternbasicSPPGrowth.rst", "stablePeriodicFrequentPatterntopKTSPIN.rst", "stablePeriodicPatternMining.rst", "temporalPatternMining.rst", "transactionalPatternMining.rst", "uncertainFrequentPatternBasicCUFPTree.rst", "uncertainFrequentPatternBasicPUFGrowth.rst", "uncertainFrequentPatternBasicTUFP.rst", "uncertainFrequentPatternBasicTubeP.rst", "uncertainFrequentPatternBasicTubeS.rst", "uncertainFrequentPatternBasicUFGrowth.rst", "uncertainFrequentPatternBasicUVECLAT.rst", "uncertainFrequentPatternMining.rst", "uncertainGeoReferencedFrequentPatternMining.rst", "uncertainGeoreferencedFrequentPatternBasicGFPGrowth.rst", "uncertainPatternMining.rst", "uncertainPeriodicFrequentPatternBasicUPFPGrowth.rst", "uncertainPeriodicFrequentPatternBasicUPFPGrowthPlus.rst", "uncertainPeriodicFrequentPatternMining.rst", "utilityPatternMining.rst", "weightedFrequentNeighbourhoodPatternBasicSWFPGrowth.rst", "weightedFrequentNeighbourhoodPatternMining.rst", "weightedFrequentPatternBasicWFIM.rst", "weightedFrequentPatternMining.rst", "weightedFrequentRegularPatternBasicWFRIMiner.rst", "weightedFrequentRegularPatternMining.rst"], "titles": ["Contiguous Frequent Patterns", "Correlated Pattern Mining", "Coverage Pattern Mining", "Fault-Tolerant Frequent Pattern Mining", "Frequent pattern With Multiple Minimum Support", "Fuzzy Correlated Pattern Mining", "Fuzzy Frequent Pattern Mining", "Fuzzy Geo-referenced Frequent Pattern Mining", "Fuzzy Geo-referenced Periodic Frequent Pattern Mining", "Fuzzy Periodic Frequent Pattern Mining", "Geo-referenced Frequent Pattern Mining", "Geo-referenced Frequent Sequence Pattern mining", "Geo-referenced Partial Periodic Pattern Mining", "Geo-referenced Periodic Frequent Pattern Mining", "High-Utility Frequent Pattern Mining", "High-Utility Geo-referenced Frequent Pattern Mining", "High-Utility Pattern mining", "High-Utility Spatial Pattern Mining", "Local Periodic Pattern Mining", "Multiple Partial Periodic Pattern Mining", "PAMI package", "PAMI.AssociationRules package", "PAMI.AssociationRules.basic package", "PAMI.correlatedPattern package", "PAMI.correlatedPattern.basic package", "PAMI.coveragePattern package", "PAMI.coveragePattern.basic package", "PAMI.extras package", "PAMI.extras.DF2DB package", "PAMI.extras.calculateMISValues package", "PAMI.extras.dbStats package", "PAMI.extras.fuzzyTransformation package", "PAMI.extras.generateDatabase package", "PAMI.extras.graph package", "PAMI.extras.image2Database package", "PAMI.extras.imageProcessing package", "PAMI.extras.messaging package", "PAMI.extras.neighbours package", "PAMI.extras.sampleDatasets package", "PAMI.extras.stats package", "PAMI.extras.syntheticDataGenerator package", "PAMI.extras.visualize package", "PAMI.faultTolerantFrequentPattern package", "PAMI.faultTolerantFrequentPattern.basic package", "PAMI.frequentPattern package", "PAMI.frequentPattern.basic package", "PAMI.frequentPattern.closed package", "PAMI.frequentPattern.cuda package", "PAMI.frequentPattern.maximal package", "PAMI.frequentPattern.pyspark package", "PAMI.frequentPattern.topk package", "PAMI.fuzzyCorrelatedPattern package", "PAMI.fuzzyCorrelatedPattern.basic package", "PAMI.fuzzyFrequentPattern package", "PAMI.fuzzyFrequentPattern.basic package", "PAMI.fuzzyGeoreferencedFrequentPattern package", "PAMI.fuzzyGeoreferencedFrequentPattern.basic package", "PAMI.fuzzyGeoreferencedPeriodicFrequentPattern package", "PAMI.fuzzyGeoreferencedPeriodicFrequentPattern.basic package", "PAMI.fuzzyPartialPeriodicPatterns package", "PAMI.fuzzyPartialPeriodicPatterns.basic package", "PAMI.fuzzyPeriodicFrequentPattern package", "PAMI.fuzzyPeriodicFrequentPattern.basic package", "PAMI.geoReferencedPeriodicFrequentPattern package", "PAMI.geoReferencedPeriodicFrequentPattern.basic package", "PAMI.georeferencedFrequentPattern package", "PAMI.georeferencedFrequentPattern.basic package", "PAMI.georeferencedFrequentSequencePattern package", "PAMI.georeferencedPartialPeriodicPattern package", "PAMI.georeferencedPartialPeriodicPattern.basic package", "PAMI.highUtilityFrequentPattern package", "PAMI.highUtilityFrequentPattern.basic package", "PAMI.highUtilityGeoreferencedFrequentPattern package", "PAMI.highUtilityGeoreferencedFrequentPattern.basic package", "PAMI.highUtilityPattern package", "PAMI.highUtilityPattern.basic package", "PAMI.highUtilityPattern.parallel package", "PAMI.highUtilityPatternsInStreams package", "PAMI.highUtilitySpatialPattern package", "PAMI.highUtilitySpatialPattern.basic package", "PAMI.highUtilitySpatialPattern.topk package", "PAMI.localPeriodicPattern package", "PAMI.localPeriodicPattern.basic package", "PAMI.multipleMinimumSupportBasedFrequentPattern package", "PAMI.multipleMinimumSupportBasedFrequentPattern.basic package", "PAMI.partialPeriodicFrequentPattern package", "PAMI.partialPeriodicFrequentPattern.basic package", "PAMI.partialPeriodicPattern package", "PAMI.partialPeriodicPattern.basic package", "PAMI.partialPeriodicPattern.closed package", "PAMI.partialPeriodicPattern.maximal package", "PAMI.partialPeriodicPattern.pyspark package", "PAMI.partialPeriodicPattern.topk package", "PAMI.partialPeriodicPatternInMultipleTimeSeries package", "PAMI.periodicCorrelatedPattern package", "PAMI.periodicCorrelatedPattern.basic package", "PAMI.periodicFrequentPattern package", "PAMI.periodicFrequentPattern.basic package", "PAMI.periodicFrequentPattern.closed package", "PAMI.periodicFrequentPattern.cuda package", "PAMI.periodicFrequentPattern.maximal package", "PAMI.periodicFrequentPattern.pyspark package", "PAMI.periodicFrequentPattern.topk package", "PAMI.periodicFrequentPattern.topk.TopkPFP package", "PAMI.periodicFrequentPattern.topk.kPFPMiner package", "PAMI.recurringPattern package", "PAMI.recurringPattern.basic package", "PAMI.relativeFrequentPattern package", "PAMI.relativeFrequentPattern.basic package", "PAMI.relativeHighUtilityPattern package", "PAMI.relativeHighUtilityPattern.basic package", "PAMI.sequence package", "PAMI.sequentialPatternMining package", "PAMI.sequentialPatternMining.basic package", "PAMI.sequentialPatternMining.closed package", "PAMI.stablePeriodicFrequentPattern package", "PAMI.stablePeriodicFrequentPattern.basic package", "PAMI.stablePeriodicFrequentPattern.topK package", "PAMI.subgraphMining package", "PAMI.subgraphMining.basic package", "PAMI.subgraphMining.topK package", "PAMI.uncertainFaultTolerantFrequentPattern package", "PAMI.uncertainFrequentPattern package", "PAMI.uncertainFrequentPattern.basic package", "PAMI.uncertainGeoreferencedFrequentPattern package", "PAMI.uncertainGeoreferencedFrequentPattern.basic package", "PAMI.uncertainPeriodicFrequentPattern package", "PAMI.uncertainPeriodicFrequentPattern.basic package", "PAMI.weightedFrequentNeighbourhoodPattern package", "PAMI.weightedFrequentNeighbourhoodPattern.basic package", "PAMI.weightedFrequentPattern package", "PAMI.weightedFrequentPattern.basic package", "PAMI.weightedFrequentRegularPattern package", "PAMI.weightedFrequentRegularPattern.basic package", "PAMI.weightedUncertainFrequentPattern package", "PAMI.weightedUncertainFrequentPattern.basic package", "Partial Periodic Frequent Pattern Mining", "Partial Periodic Pattern Mining", "Periodic correlated pattern mining", "Periodic Frequent Pattern Mining", "Recurring Pattern Mining", "Relative High-Utility Pattern Mining", "Sequential Frequent Pattern mining", "Stable Periodic Pattern Mining", "Uncertain Frequent Pattern mining", "Uncertain Geo-Referenced Frequent Pattern mining", "Uncertain Periodic Frequent Pattern mining", "Weighted Frequent Neighbourhood Pattern Mining", "Weighted Frequent Pattern Mining", "Weighted Frequent Regular Pattern Mining", "<no title>", "Contiguous Patterns", "CoMine", "CoMinePlus", "Basic", "CMine", "CPPG", "Basic", "FTApriori", "FTFPGrowth", "Basic", "Frequent Pattern mining", "Apriori", "Aprioribitset", "ECLAT", "ECLATDiffset", "ECLATbitset", "FPGrowth", "cuApriori", "cuAprioriBit", "cudaAprioriGCT", "cudaAprioriTID", "cuEclat", "cuEclatBit", "cudaEclatGCT", "MaxFPGrowth", "Basic", "parallelApriori", "parallelECLAT", "parallelFPGrowth", "FAE", "Basic", "CHARM", "Basic", "FCPGrowth", "Basic", "FFIMiner", "Basic", "Basic", "FFSPMiner", "FGPFPMiner", "Fuzzy Pattern Mining", "Basic", "FPFPMiner", "Basic", "<no title>", "Basic", "Geo-referenced Pattern Mining", "Basic", "GPFPMiner", "FSPGrowth", "SpatialECLAT", "STEclat", "HUFIM", "Basic", "Basic", "SHUFIM", "EFIM", "HMiner", "UPGrowth", "Basic", "HDSHUIM", "SHUIM", "Basic", "TKSHUIM", "Welcome to PAMI\u2019s documentation!", "Basic", "LPPGrowth", "LPPMBreadth", "LPPMDepth", "PAMI", "CFPGrowth", "CFPGrowthPlus", "Basic", "Multiple Timeseries", "Basic", "GPFgrowth", "PPF_DFS", "PPGrowth", "Basic", "GThreePGrowth", "PPPGrowth", "PPP_ECLAT", "PPPClose", "Max3PGrowth", "k3PMiner", "Basic", "EPCPGrowth", "Basic", "PFECLAT", "PFPGrowth", "PFPGrowthPlus", "PFPMC", "PSGrowth", "CPFPMiner", "MaxPFGrowth", "TopkPFP", "kPFPMiner", "Basic", 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265, 266, 267, 268, 269, 270, 271, 273, 276, 277, 278, 279, 281, 282, 284, 286], "singl": [4, 45, 71, 75, 80, 110, 119, 120, 166, 181, 203, 207, 214, 253], "uniform": [4, 181, 265], "all": [4, 24, 26, 28, 30, 35, 39, 49, 54, 56, 58, 60, 62, 71, 73, 75, 78, 79, 80, 82, 84, 86, 89, 90, 91, 92, 106, 108, 110, 116, 119, 120, 127, 152, 153, 155, 177, 179, 181, 186, 189, 190, 191, 193, 203, 206, 207, 208, 211, 212, 214, 217, 221, 222, 233, 234, 249, 250, 251, 252, 253, 261, 262, 265, 266, 277, 279], "vari": [4, 18, 136, 143, 145, 181, 216, 225, 264, 275, 281], "level": [4, 33, 101, 181], "By": [4, 45, 162, 181], "more": [4, 18, 66, 143, 181, 201, 216, 264, 265], "nuanc": [4, 181], "each": [4, 12, 14, 17, 19, 30, 39, 49, 73, 75, 79, 80, 82, 119, 120, 139, 141, 145, 146, 177, 178, 179, 181, 191, 196, 204, 206, 209, 211, 212, 213, 214, 217, 218, 219, 223, 238, 250, 251, 254, 256, 265, 266, 275, 277, 280, 281], "evalu": [4, 181], "individu": [4, 181, 191, 277, 281], "its": [4, 17, 29, 30, 39, 54, 56, 58, 62, 82, 119, 136, 147, 149, 181, 186, 189, 190, 193, 213, 217, 218, 219, 225, 266, 281, 283, 287], "import": [4, 14, 15, 17, 24, 26, 27, 28, 29, 30, 31, 32, 33, 35, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 181, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 204, 205, 206, 207, 208, 209, 211, 212, 213, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 265, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "context": [4, 14, 15, 17, 139, 181, 204, 205, 213, 238], "traffic": [4, 8, 9, 19, 136, 137, 139, 143, 148, 181, 188, 192, 223, 225, 229, 238, 264, 285], "involv": [5, 7, 8, 9, 10, 11, 14, 15, 17, 19, 79, 137, 139, 141, 142, 144, 145, 146, 147, 148, 149, 183, 187, 188, 192, 194, 195, 204, 205, 211, 213, 223, 229, 238, 254, 255, 274, 275, 280, 283, 285, 287], "explor": [5, 71, 110, 119, 183, 203, 253], "itemset": [5, 24, 45, 46, 48, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 86, 88, 91, 101, 110, 123, 129, 131, 133, 135, 141, 149, 152, 153, 166, 175, 182, 183, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 227, 230, 231, 253, 254, 256, 271, 273, 282, 284, 286, 287], "exhibit": [5, 7, 8, 9, 12, 136, 137, 138, 139, 143, 147, 149, 183, 187, 188, 192, 196, 225, 229, 236, 238, 264, 283, 287], "linear": [5, 183], "assess": [5, 183], "through": [5, 119, 123, 183, 271], "instead": [5, 183], "sole": [5, 138, 183, 236], "co": [5, 183], "strength": [5, 183], "uncov": [5, 183], "basket": [5, 14, 91, 101, 141, 148, 183, 204, 250, 251, 254, 285], "analyt": [5, 14, 104, 148, 149, 183, 204, 247, 285, 287], "financi": [5, 6, 9, 137, 140, 141, 143, 146, 183, 185, 192, 229, 248, 254, 264, 280], "ffp": [6, 185], "captur": [6, 8, 136, 185, 188, 225], "inher": [6, 185], "partial": [6, 60, 69, 86, 88, 89, 90, 91, 92, 101, 185, 196, 197, 202, 215, 223, 224, 225, 226, 227, 229, 230, 231, 232, 233, 234, 235, 265], "event": [6, 8, 9, 10, 11, 12, 13, 15, 17, 19, 82, 136, 139, 142, 145, 147, 185, 188, 192, 194, 195, 196, 198, 205, 213, 217, 218, 219, 223, 224, 225, 238, 255, 275, 283], "requir": [6, 40, 73, 75, 136, 185, 206, 209, 225], "variat": [6, 12, 137, 185, 196, 229], "degre": [6, 136, 137, 185, 225, 229], "membership": [6, 54, 185, 186], "similar": [6, 185, 197], "them": [6, 119, 137, 143, 185, 229, 264], "suitabl": [6, 143, 185, 264], "imprecis": [6, 8, 9, 185, 188, 192], "medic": [6, 16, 185, 210], "qualiti": [6, 185], "control": [6, 26, 82, 86, 97, 98, 100, 101, 103, 108, 155, 156, 185, 217, 218, 219, 226, 227, 239, 240, 241, 242, 243, 244, 245, 246, 252], "geograph": [7, 8, 10, 11, 13, 145, 187, 188, 194, 195, 198, 275], "mai": [7, 9, 12, 13, 18, 19, 136, 137, 143, 145, 146, 187, 192, 196, 198, 216, 223, 225, 229, 264, 265, 275, 280], "object": [7, 27, 28, 29, 30, 32, 33, 35, 36, 37, 39, 40, 41, 49, 52, 80, 82, 91, 97, 101, 116, 119, 120, 147, 179, 184, 187, 191, 214, 217, 243, 262, 277, 281, 283], "epidemiolog": [7, 8, 187, 188], "environment": [7, 8, 10, 11, 12, 13, 15, 136, 144, 146, 147, 187, 188, 194, 195, 196, 198, 205, 225, 274, 280, 283], "monitor": [7, 8, 10, 11, 12, 13, 15, 19, 136, 137, 138, 139, 142, 146, 147, 187, 188, 194, 195, 196, 198, 205, 223, 225, 229, 236, 238, 255, 280, 283], "recur": [8, 9, 12, 13, 19, 106, 136, 137, 138, 139, 188, 192, 196, 198, 215, 223, 225, 229, 236, 238, 248, 249, 265], "tempor": [8, 9, 10, 11, 12, 13, 18, 28, 31, 32, 40, 62, 79, 86, 88, 89, 90, 91, 92, 95, 97, 98, 100, 103, 104, 116, 127, 136, 138, 139, 188, 191, 192, 193, 194, 195, 196, 197, 198, 211, 215, 216, 224, 225, 226, 230, 231, 233, 234, 235, 236, 237, 238, 239, 241, 243, 244, 245, 246, 247, 261, 262, 277, 278, 279, 281], "locat": [8, 10, 15, 145, 188, 194, 197, 205, 275], "repetit": [8, 136, 143, 188, 225, 264], "natur": [8, 9, 123, 138, 145, 188, 192, 236, 269, 270, 275, 281], "phenomena": [8, 11, 13, 139, 188, 195, 198, 238], "over": [8, 18, 80, 119, 136, 138, 139, 142, 143, 188, 197, 214, 216, 224, 225, 236, 238, 255, 264], "time": [8, 9, 11, 12, 13, 18, 24, 26, 28, 30, 39, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 136, 137, 138, 139, 140, 142, 143, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 188, 189, 190, 192, 193, 195, 196, 197, 198, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 216, 217, 218, 219, 221, 222, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 252, 253, 255, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "space": [8, 12, 24, 26, 27, 29, 30, 31, 37, 39, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 188, 189, 190, 191, 193, 196, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 224, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 256, 261, 262, 263, 265, 266, 267, 268, 269, 270, 271, 273, 276, 277, 278, 279, 281, 282, 284, 286], "while": [8, 11, 43, 64, 66, 69, 75, 82, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 106, 110, 116, 117, 119, 121, 123, 125, 127, 129, 131, 133, 135, 158, 159, 188, 195, 199, 201, 202, 209, 217, 218, 219, 228, 230, 231, 232, 233, 234, 237, 241, 242, 243, 244, 245, 249, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 277, 278, 279, 282, 284, 286], "entiti": [8, 188], "flow": [8, 143, 188, 264], "studi": [8, 188], "character": [9, 14, 15, 18, 138, 192, 204, 205, 216, 236], "seri": [9, 11, 18, 28, 30, 93, 97, 106, 137, 140, 192, 195, 216, 224, 228, 229, 243, 248, 249], "product": [9, 192, 281], "among": [10, 194], "It": [10, 11, 19, 24, 27, 28, 30, 35, 39, 40, 43, 45, 46, 49, 66, 79, 82, 86, 89, 90, 92, 97, 98, 101, 103, 104, 106, 119, 123, 131, 133, 135, 142, 152, 153, 159, 162, 167, 179, 182, 194, 195, 197, 201, 211, 217, 223, 226, 227, 233, 234, 235, 239, 240, 241, 244, 246, 247, 249, 255, 267, 268, 269, 270, 273, 281, 284, 286], "analyz": [10, 11, 19, 142, 161, 194, 195, 223, 255], "coordin": [10, 194], "timestamp": [10, 46, 82, 88, 97, 101, 116, 127, 139, 182, 191, 194, 197, 217, 224, 232, 238, 239, 242, 243, 261, 265, 277, 279, 281], "possibl": [10, 106, 194, 249], "relat": [10, 106, 119, 139, 147, 194, 238, 249, 283], "servic": [10, 15, 145, 194, 205, 275], "conserv": [10, 13, 194, 198], "tourism": [10, 194], "hospit": [10, 194], "sequenti": [11, 30, 39, 195, 215, 255], "preserv": [11, 195], "order": [11, 54, 60, 73, 79, 80, 119, 142, 186, 195, 206, 212, 214, 224, 255, 256, 265], "instanc": [11, 119, 120, 142, 195, 255], "transport": [11, 13, 147, 195, 198, 283], "urban": [11, 13, 15, 145, 147, 195, 198, 205, 275, 283], "plan": [11, 13, 15, 16, 145, 147, 195, 198, 205, 210, 275, 283], "alwai": [12, 196, 265], "entir": [12, 19, 196, 223, 281], "interest": [12, 78, 79, 80, 116, 196, 211, 261, 262], "In": [12, 24, 30, 39, 45, 75, 116, 119, 121, 123, 127, 131, 135, 139, 145, 147, 149, 152, 153, 162, 196, 197, 209, 224, 238, 262, 265, 271, 275, 278, 281, 283, 284, 287], "word": [12, 196, 197, 224, 265], "agricultur": [12, 17, 196, 213], "crop": [12, 196], "public": [12, 54, 186, 196], "health": [12, 196], "surveil": [12, 196], "disast": [12, 17, 145, 196, 213, 275], "describ": [13, 198, 277], "consist": [13, 14, 17, 18, 143, 191, 198, 204, 213, 216, 264, 277, 281], "activ": [13, 198], "area": [13, 198], "interv": [13, 18, 19, 28, 82, 136, 137, 138, 139, 140, 143, 198, 216, 217, 218, 219, 223, 225, 229, 236, 238, 248, 264], "reveal": [13, 198], "movement": [13, 198], "human": [13, 198], "logist": [13, 198], "infrastructur": [13, 198], "transact": [14, 24, 26, 27, 28, 29, 30, 31, 32, 35, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 121, 123, 125, 127, 129, 131, 133, 135, 141, 142, 143, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 191, 193, 197, 199, 201, 202, 203, 204, 206, 207, 208, 209, 211, 212, 214, 215, 217, 218, 219, 221, 222, 224, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 254, 255, 256, 261, 262, 263, 264, 265, 267, 268, 269, 270, 271, 273, 276, 277, 278, 279, 281, 282, 284, 286], "databas": [14, 16, 24, 26, 27, 28, 29, 30, 31, 32, 35, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 136, 138, 139, 143, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 191, 193, 197, 199, 201, 202, 203, 204, 206, 207, 208, 209, 210, 211, 212, 214, 215, 217, 221, 222, 224, 225, 226, 227, 228, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 264, 267, 268, 269, 270, 271, 273, 276, 278, 279, 281, 282, 284, 286], "contribut": [14, 16, 17, 141, 204, 210, 213, 254], "significantli": [14, 17, 141, 204, 213, 254], "reflect": [14, 15, 17, 204, 205, 213], "domain": [14, 15, 17, 204, 205, 213], "georeferenc": [15, 205], "combin": [15, 45, 46, 66, 86, 88, 92, 103, 104, 108, 148, 166, 182, 197, 201, 205, 227, 232, 235, 246, 247, 252, 285], "distribut": [15, 17, 30, 39, 49, 101, 177, 205, 213], "lb": [15, 205], "develop": [15, 145, 205, 275], "The": [16, 24, 26, 27, 29, 30, 31, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 136, 139, 140, 148, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 191, 193, 197, 199, 201, 202, 203, 206, 207, 208, 209, 210, 211, 212, 214, 217, 218, 219, 221, 222, 225, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 252, 253, 256, 261, 262, 263, 265, 266, 267, 268, 269, 270, 271, 273, 276, 277, 278, 279, 281, 282, 284, 285, 286], "hupm": [16, 20, 210, 220], "maxim": [16, 20, 44, 82, 87, 96, 137, 139, 161, 175, 210, 217, 218, 219, 234, 245], "from": [16, 24, 26, 27, 28, 29, 30, 31, 32, 33, 35, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 144, 145, 146, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 191, 193, 199, 201, 202, 203, 206, 207, 208, 209, 210, 211, 212, 214, 217, 218, 219, 221, 222, 224, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 265, 266, 267, 268, 269, 270, 271, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 284, 286], "perspect": [16, 210], "diagnosi": [16, 210], "howev": [16, 24, 26, 27, 29, 31, 37, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 191, 193, 199, 201, 202, 203, 206, 207, 208, 209, 210, 211, 212, 214, 217, 218, 219, 221, 222, 224, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 265, 266, 267, 268, 269, 270, 271, 273, 276, 277, 278, 279, 281, 282, 284, 286], "pai": [16, 210], "less": [16, 37, 116, 191, 210, 261, 262], "attent": [16, 210], "interpret": [16, 210], "explain": [16, 210], "scenario": [16, 210], "clinic": [16, 210], "drug": [16, 161, 210], "prescript": [16, 210], "therapi": [16, 210], "diseas": [16, 210], "predict": [16, 27, 136, 140, 143, 210, 225, 248, 264], "identif": [17, 137, 213, 229], "ha": [17, 46, 86, 97, 106, 141, 182, 213, 227, 242, 249, 254], "predefin": [17, 18, 82, 141, 213, 216, 217, 218, 219, 254], "measur": [17, 82, 110, 136, 141, 213, 217, 218, 219, 225, 253, 254], "resourc": [17, 18, 213, 216], "precis": [17, 144, 213, 274], "emerg": [17, 145, 213, 275], "respons": [17, 91, 101, 119, 145, 213, 275], "top": [17, 27, 50, 79, 80, 92, 103, 104, 117, 120, 123, 139, 161, 180, 211, 214, 235, 246, 247, 263, 269, 270], "k": [17, 24, 27, 50, 56, 69, 71, 79, 80, 92, 93, 97, 103, 104, 110, 117, 120, 123, 127, 129, 133, 139, 152, 153, 161, 180, 189, 202, 203, 211, 214, 228, 235, 243, 246, 247, 253, 263, 269, 270, 278, 282, 286], "lpp": [18, 216], "some": [18, 30, 39, 82, 106, 137, 216, 217, 218, 219, 229, 249, 265], "non": [18, 82, 106, 123, 125, 135, 191, 216, 217, 218, 219, 224, 249, 265, 267, 268, 269, 270, 271, 276, 277, 281], "A": [18, 20, 26, 40, 43, 45, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 82, 91, 97, 101, 110, 120, 123, 127, 156, 159, 162, 167, 184, 186, 189, 190, 191, 193, 197, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 216, 217, 218, 219, 224, 243, 253, 256, 265, 266, 268, 277, 278, 281], "said": [18, 82, 197, 216, 217, 218, 219], "appear": [18, 26, 82, 97, 98, 100, 101, 108, 110, 155, 156, 161, 216, 217, 218, 219, 241, 242, 243, 244, 245, 252, 253], "regularli": [18, 82, 216, 217, 218, 219], "continu": [18, 82, 120, 216, 217, 218, 219], "s": [18, 26, 33, 56, 71, 73, 75, 76, 79, 82, 88, 89, 90, 91, 92, 93, 97, 98, 100, 101, 103, 104, 108, 110, 116, 117, 120, 156, 189, 203, 206, 207, 208, 209, 211, 212, 216, 217, 218, 219, 228, 230, 231, 232, 233, 234, 235, 241, 242, 243, 244, 245, 246, 247, 252, 253, 262, 263], "demonstr": [18, 136, 140, 143, 216, 225, 248, 264], "one": [18, 24, 26, 27, 29, 31, 37, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 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158, 159, 162, 163, 164, 166, 167, 175, 179, 202, 221, 228, 230, 231, 232, 239, 240, 241, 242, 243, 245, 249, 267, 268, 269, 270, 273, 284, 286], "correl": [24, 52, 86, 95, 152, 153, 154, 183, 184, 191, 215, 226, 227, 236, 237, 265, 266], "fp": [24, 28, 43, 45, 49, 131, 152, 153, 159, 167, 179, 284], "growth": [24, 48, 49, 75, 82, 90, 97, 100, 127, 152, 153, 175, 179, 209, 217, 234, 243, 245, 279], "depth": [24, 46, 82, 89, 98, 119, 152, 153, 182, 217, 218, 219, 233, 244], "first": [24, 45, 46, 49, 75, 80, 82, 89, 98, 110, 119, 120, 152, 153, 162, 179, 182, 207, 214, 217, 218, 219, 224, 233, 244, 253, 265, 277], "search": [24, 43, 45, 46, 49, 54, 56, 58, 62, 75, 76, 82, 84, 89, 98, 119, 121, 131, 133, 152, 153, 158, 159, 162, 167, 177, 178, 179, 182, 186, 189, 190, 193, 215, 217, 218, 219, 222, 233, 244, 284, 286], "lee": [24, 97, 127, 152, 153, 240, 278], "y": [24, 33, 43, 45, 71, 97, 104, 116, 117, 119, 120, 152, 153, 159, 167, 203, 239, 247, 262, 263], "kim": [24, 152, 153], "w": [24, 79, 116, 127, 152, 153, 212, 261, 278], "cao": [24, 152, 153], "d": [24, 152, 153, 256, 265, 266], "han": [24, 43, 45, 84, 152, 153, 158, 159, 167, 221], "j": [24, 43, 45, 46, 48, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 91, 97, 110, 116, 119, 120, 123, 127, 131, 152, 153, 159, 167, 175, 182, 203, 206, 207, 212, 214, 217, 218, 219, 221, 226, 232, 233, 241, 253, 261, 267, 278, 284], "2003": [24, 45, 152, 153, 165], "icdm": [24, 123, 152, 153, 271], "pp": [24, 45, 49, 56, 62, 69, 79, 80, 93, 97, 110, 116, 129, 131, 133, 152, 153, 162, 177, 189, 193, 202, 211, 214, 228, 243, 253, 261, 282, 284, 286], "581": [24, 152, 153], "584": [24, 152, 153], "paramet": [24, 26, 27, 28, 29, 31, 32, 33, 35, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "name": [24, 26, 27, 28, 29, 30, 31, 32, 33, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 277, 278, 279, 282, 284, 286], "input": [24, 26, 27, 29, 30, 31, 32, 33, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "file": [24, 26, 27, 28, 29, 30, 31, 32, 33, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "complet": [24, 26, 28, 29, 30, 31, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 136, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 225, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 277, 278, 279, 282, 284, 286], "ofil": [24, 26, 27, 28, 29, 30, 31, 35, 37, 39, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "output": [24, 26, 27, 28, 29, 30, 31, 32, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "store": [24, 26, 27, 29, 30, 31, 33, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 224, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "user": [24, 26, 27, 28, 29, 31, 37, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 139, 142, 143, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 191, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 255, 261, 262, 263, 264, 267, 268, 269, 270, 271, 273, 276, 277, 278, 279, 281, 282, 284, 286], "specifi": [24, 29, 32, 33, 37, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 78, 79, 80, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "either": [24, 29, 40, 43, 45, 46, 48, 49, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 78, 79, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 106, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 208, 211, 212, 226, 227, 228, 230, 231, 232, 233, 234, 237, 239, 240, 241, 242, 243, 244, 245, 249, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 281, 282, 284, 286], "count": [24, 29, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 78, 79, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 110, 116, 117, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 208, 211, 212, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "proport": [24, 29, 43, 45, 46, 48, 49, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 106, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 136, 152, 153, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 208, 211, 212, 225, 226, 227, 228, 230, 231, 232, 233, 234, 237, 239, 240, 241, 242, 243, 244, 245, 249, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "size": [24, 29, 30, 33, 39, 43, 45, 46, 48, 49, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 106, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 208, 211, 212, 226, 227, 228, 230, 231, 232, 233, 234, 237, 239, 240, 241, 242, 243, 244, 245, 249, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "If": [24, 29, 43, 45, 46, 48, 49, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 106, 116, 117, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 182, 184, 186, 189, 190, 191, 193, 199, 201, 202, 203, 206, 208, 211, 212, 226, 227, 228, 230, 231, 232, 233, 234, 237, 239, 240, 241, 242, 243, 244, 245, 249, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 277, 278, 279, 282, 284, 286], "program": [24, 26, 29, 30, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "integ": [24, 29, 30, 43, 45, 46, 48, 49, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 78, 79, 80, 82, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 106, 110, 116, 117, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 208, 211, 212, 217, 224, 226, 227, 228, 230, 231, 232, 233, 234, 237, 239, 240, 241, 242, 243, 244, 245, 249, 253, 261, 262, 263, 265, 266, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "treat": [24, 29, 43, 45, 46, 48, 49, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 106, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 208, 211, 212, 226, 227, 228, 230, 231, 232, 233, 234, 237, 239, 240, 241, 242, 243, 244, 245, 249, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "express": [24, 29, 43, 45, 46, 48, 49, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 106, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 208, 211, 212, 226, 227, 228, 230, 231, 232, 233, 234, 237, 239, 240, 241, 242, 243, 244, 245, 249, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "rang": [24, 30, 39, 40, 52, 84, 123, 125, 127, 129, 131, 135, 152, 153, 184, 221, 222, 267, 276, 277, 278, 279, 282, 284], "0": [24, 26, 27, 30, 33, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 64, 66, 69, 75, 76, 80, 82, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 189, 191, 197, 199, 201, 202, 207, 214, 217, 218, 219, 226, 227, 228, 230, 231, 232, 233, 234, 237, 239, 240, 241, 242, 243, 244, 245, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 277, 278, 279, 281, 282, 284, 286], "1": [24, 30, 39, 43, 45, 46, 52, 56, 62, 75, 76, 79, 82, 84, 86, 88, 91, 97, 108, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 158, 162, 163, 164, 165, 166, 167, 182, 184, 189, 191, 193, 197, 212, 217, 218, 219, 221, 224, 226, 227, 230, 231, 239, 240, 243, 252, 256, 265, 266, 267, 268, 269, 270, 271, 273, 276, 277, 278, 279, 281, 282, 284, 286], "variabl": [24, 26, 27, 29, 30, 31, 37, 39, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 137, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "distinguish": [24, 26, 27, 29, 31, 37, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 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273, 276, 278, 279, 282, 284, 286], "default": [24, 26, 27, 29, 30, 31, 37, 39, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 191, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 224, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 265, 266, 267, 268, 269, 270, 271, 273, 276, 277, 278, 279, 281, 282, 284, 286], "seper": [24, 26, 27, 29, 31, 32, 37, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 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261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "consum": [24, 26, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "memoryrss": [24, 26, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 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212, 214, 226, 227, 234, 250, 251, 252, 253], "minimum": [24, 26, 27, 29, 30, 39, 43, 50, 54, 56, 58, 60, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 97, 98, 100, 101, 106, 108, 110, 116, 119, 120, 121, 123, 125, 127, 129, 131, 135, 139, 152, 153, 155, 156, 158, 180, 181, 186, 189, 190, 206, 209, 211, 212, 214, 215, 217, 218, 219, 221, 222, 230, 231, 232, 233, 234, 235, 238, 241, 242, 243, 244, 245, 249, 252, 253, 261, 262, 266, 267, 276, 278, 279, 282, 284], "ratio": [24, 52, 136, 152, 153, 184, 225], "should": [24, 52, 119, 152, 153, 184], "list": [24, 26, 27, 28, 30, 32, 35, 39, 40, 43, 45, 46, 48, 49, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 88, 90, 91, 92, 93, 95, 97, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 179, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 221, 222, 228, 230, 231, 232, 234, 235, 237, 239, 240, 241, 242, 243, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "mapsupport": [24, 43, 45, 46, 48, 84, 88, 90, 91, 93, 95, 97, 100, 101, 106, 108, 116, 117, 123, 125, 127, 129, 131, 133, 135, 152, 153, 159, 167, 175, 182, 221, 222, 228, 230, 231, 232, 234, 237, 239, 240, 241, 242, 243, 245, 249, 252, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "dictionari": [24, 26, 27, 30, 31, 39, 43, 45, 46, 48, 49, 50, 54, 64, 66, 69, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 186, 199, 201, 202, 206, 212, 214, 217, 221, 222, 226, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 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269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "itemsetcount": [24, 46, 48, 90, 93, 95, 97, 100, 101, 106, 108, 116, 117, 123, 125, 127, 135, 152, 153, 175, 182, 228, 234, 237, 239, 240, 241, 242, 243, 245, 249, 252, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 279], "finalpattern": [24, 26, 31, 43, 45, 46, 48, 49, 50, 64, 66, 69, 78, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 199, 201, 202, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "dict": [24, 26, 27, 30, 31, 33, 39, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 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135, 152, 153, 155, 162, 163, 164, 165, 166, 167, 180, 182, 189, 226, 227, 228, 239, 240, 244, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "format": [24, 26, 30, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 191, 193, 197, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 224, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 256, 261, 262, 263, 265, 266, 267, 268, 269, 270, 271, 273, 276, 277, 278, 279, 281, 282, 284, 286], "venv": [24, 26, 30, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 91, 93, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 231, 232, 233, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "python3": [24, 26, 30, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "py": [24, 26, 30, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "inputfil": [24, 26, 27, 30, 39, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 90, 91, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "outputfil": [24, 26, 27, 28, 30, 32, 35, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 90, 91, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "exampl": [24, 26, 30, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 191, 193, 197, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 224, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 256, 261, 262, 263, 265, 266, 267, 268, 269, 270, 271, 273, 276, 277, 278, 279, 281, 282, 284, 286], "sampletdb": [24, 26, 48, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 86, 89, 90, 93, 95, 97, 98, 100, 101, 106, 110, 116, 117, 123, 125, 127, 135, 152, 153, 155, 156, 175, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 226, 227, 228, 233, 234, 237, 241, 242, 243, 244, 245, 249, 253, 261, 262, 263, 267, 276, 278, 279], "txt": [24, 26, 30, 32, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "25": [24, 86, 152, 153, 226, 227], "2": [24, 40, 48, 50, 52, 54, 56, 58, 60, 62, 69, 73, 79, 80, 88, 89, 91, 97, 98, 100, 106, 108, 116, 121, 127, 129, 152, 153, 175, 180, 184, 186, 189, 190, 191, 193, 197, 202, 206, 212, 214, 224, 230, 231, 233, 241, 242, 243, 244, 245, 249, 252, 261, 265, 266, 277, 278, 279, 281, 282], "call": [24, 26, 45, 46, 50, 56, 58, 78, 80, 82, 86, 97, 98, 119, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 162, 163, 164, 165, 166, 167, 180, 182, 189, 190, 219, 226, 227, 239, 240, 244, 267, 268, 269, 270, 271, 276, 277, 278, 279, 282, 284, 286], "alg": [24, 26, 30, 39, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "obj": [24, 26, 27, 28, 29, 30, 31, 33, 35, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "getpattern": [24, 26, 29, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "print": [24, 26, 28, 30, 32, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "number": [24, 26, 30, 32, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 265, 266, 267, 268, 269, 270, 271, 273, 276, 278, 279, 281, 282, 284, 286], "len": [24, 26, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "savepattern": [24, 45, 46, 48, 75, 76, 84, 101, 104, 106, 110, 117, 120, 125, 127, 131, 152, 153, 165, 167, 175, 182, 222, 247, 249, 253, 263, 276, 279, 284], "df": [24, 26, 28, 43, 45, 46, 48, 49, 50, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "getpatternsasdatafram": [24, 26, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "memuss": [24, 26, 28, 43, 45, 46, 48, 49, 50, 52, 54, 56, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "getmemoryuss": [24, 26, 28, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "memrss": [24, 26, 28, 43, 45, 46, 48, 49, 50, 52, 54, 56, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "getmemoryrss": [24, 26, 28, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "run": [24, 26, 28, 30, 39, 43, 45, 46, 48, 49, 50, 52, 54, 56, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "getruntim": [24, 26, 28, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "executiontim": [24, 26, 28, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "second": [24, 26, 28, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 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50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "b": [24, 52, 54, 56, 58, 62, 66, 75, 79, 88, 108, 121, 152, 153, 184, 186, 189, 190, 193, 201, 208, 211, 224, 232, 252, 256, 265, 266], "sai": [24, 40, 52, 54, 56, 58, 62, 66, 75, 79, 108, 152, 153, 184, 186, 189, 190, 193, 201, 208, 211, 212, 252], "chitra": [24, 52, 54, 56, 58, 62, 66, 75, 79, 108, 152, 153, 184, 186, 189, 190, 193, 201, 208, 211, 252], "revis": [24, 45, 46, 50, 86, 97, 152, 153, 162, 163, 164, 165, 166, 167, 180, 182, 226, 227, 239, 240], "tarun": [24, 45, 46, 50, 75, 86, 97, 152, 153, 162, 163, 164, 165, 166, 167, 180, 182, 226, 227, 239, 240], "sreepada": [24, 45, 46, 50, 75, 86, 97, 152, 153, 162, 163, 164, 165, 166, 167, 180, 182, 226, 227, 239, 240], "under": [24, 26, 30, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "supervis": [24, 26, 30, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 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54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "function": [24, 26, 30, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 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26, 36, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "after": [24, 26, 39, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 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263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "runtim": [24, 26, 33, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "taken": [24, 26, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 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270, 271, 273, 276, 278, 279, 284, 285], "printresult": [24, 26, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "result": [24, 26, 27, 30, 39, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 106, 108, 110, 116, 117, 119, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "recurs": [24, 71, 73, 75, 79, 80, 86, 88, 97, 110, 116, 119, 123, 152, 153, 203, 206, 207, 209, 212, 214, 227, 232, 239, 242, 253, 261, 271], "node": [24, 49, 75, 82, 88, 90, 91, 93, 95, 97, 100, 101, 106, 116, 117, 123, 125, 127, 135, 152, 153, 177, 178, 179, 209, 217, 228, 230, 231, 234, 237, 240, 241, 243, 245, 249, 262, 263, 267, 268, 269, 270, 271, 276, 278, 279], "root": [24, 49, 82, 88, 90, 91, 93, 95, 97, 100, 101, 106, 116, 117, 123, 125, 127, 135, 152, 153, 179, 217, 228, 230, 231, 234, 237, 240, 241, 243, 245, 249, 262, 263, 267, 268, 269, 270, 271, 276, 278, 279], "build": [24, 49, 75, 152, 153, 179, 209], "ani": [24, 26, 82, 86, 97, 98, 100, 101, 103, 148, 152, 153, 155, 156, 217, 218, 219, 226, 227, 239, 240, 241, 242, 243, 244, 245, 246, 265, 285], "current": [24, 80, 152, 153, 214, 277], "being": [24, 152, 153, 265], "_node": [24, 152, 153], "save": [24, 26, 27, 28, 29, 30, 32, 33, 35, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 265, 266, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "outfil": [24, 26, 28, 29, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 276, 278, 279, 282, 284, 286], "an": [24, 26, 28, 29, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 62, 64, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 92, 95, 97, 98, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 139, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 191, 193, 197, 199, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 224, 226, 227, 230, 232, 235, 237, 238, 239, 240, 241, 242, 243, 244, 250, 251, 252, 253, 256, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 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\ No newline at end of file
+Search.setIndex({"docnames": ["ContiguousFrequentPatterns1", "CorrelatedPatternMining1", "CoveragePatternMining1", "FaultTolerantPatternMining1", "FrequentPatternWithMultipleMinimumSupport1", "FuzzyCorrelatedPatternMining1", "FuzzyFrequentPatternMining1", "FuzzyGeoReferencedFrequentPatternMining1", "FuzzyGeoReferencedPeriodicFrequentPatternMining1", "FuzzyPeriodicFrequentPatternMining1", "GeoReferencedFrequentPatternMining1", "GeoReferencedFrequentSequencePatternMining1", "GeoReferencedPartialPeriodicPatternMining1", "GeoReferencedPeriodicFrequentPatternMining1", "HighUtilityFrequentPatternMining1", "HighUtilityGeo-referencedFrequentPatternMining1", "HighUtilityPatternMining1", "HighUtilitySpatialPatternMining1", "LocalPeriodicPatternMining1", "MultiplePartialPeriodicPatternMining1", "PAMI", "PAMI.AssociationRules", "PAMI.AssociationRules.basic", "PAMI.correlatedPattern", "PAMI.correlatedPattern.basic", "PAMI.coveragePattern", "PAMI.coveragePattern.basic", "PAMI.extras", "PAMI.extras.DF2DB", "PAMI.extras.calculateMISValues", "PAMI.extras.dbStats", "PAMI.extras.fuzzyTransformation", "PAMI.extras.generateDatabase", "PAMI.extras.graph", "PAMI.extras.image2Database", "PAMI.extras.imageProcessing", "PAMI.extras.messaging", "PAMI.extras.neighbours", "PAMI.extras.sampleDatasets", "PAMI.extras.stats", "PAMI.extras.syntheticDataGenerator", "PAMI.extras.visualize", "PAMI.faultTolerantFrequentPattern", "PAMI.faultTolerantFrequentPattern.basic", "PAMI.frequentPattern", "PAMI.frequentPattern.basic", "PAMI.frequentPattern.closed", "PAMI.frequentPattern.cuda", "PAMI.frequentPattern.maximal", "PAMI.frequentPattern.pyspark", "PAMI.frequentPattern.topk", "PAMI.fuzzyCorrelatedPattern", "PAMI.fuzzyCorrelatedPattern.basic", "PAMI.fuzzyFrequentPattern", "PAMI.fuzzyFrequentPattern.basic", "PAMI.fuzzyGeoreferencedFrequentPattern", "PAMI.fuzzyGeoreferencedFrequentPattern.basic", "PAMI.fuzzyGeoreferencedPeriodicFrequentPattern", "PAMI.fuzzyGeoreferencedPeriodicFrequentPattern.basic", "PAMI.fuzzyPartialPeriodicPatterns", "PAMI.fuzzyPartialPeriodicPatterns.basic", "PAMI.fuzzyPeriodicFrequentPattern", "PAMI.fuzzyPeriodicFrequentPattern.basic", "PAMI.geoReferencedPeriodicFrequentPattern", "PAMI.geoReferencedPeriodicFrequentPattern.basic", "PAMI.georeferencedFrequentPattern", "PAMI.georeferencedFrequentPattern.basic", "PAMI.georeferencedFrequentSequencePattern", "PAMI.georeferencedPartialPeriodicPattern", "PAMI.georeferencedPartialPeriodicPattern.basic", "PAMI.highUtilityFrequentPattern", "PAMI.highUtilityFrequentPattern.basic", "PAMI.highUtilityGeoreferencedFrequentPattern", "PAMI.highUtilityGeoreferencedFrequentPattern.basic", "PAMI.highUtilityPattern", "PAMI.highUtilityPattern.basic", "PAMI.highUtilityPattern.parallel", "PAMI.highUtilityPatternsInStreams", "PAMI.highUtilitySpatialPattern", "PAMI.highUtilitySpatialPattern.basic", "PAMI.highUtilitySpatialPattern.topk", "PAMI.localPeriodicPattern", "PAMI.localPeriodicPattern.basic", "PAMI.multipleMinimumSupportBasedFrequentPattern", "PAMI.multipleMinimumSupportBasedFrequentPattern.basic", "PAMI.partialPeriodicFrequentPattern", "PAMI.partialPeriodicFrequentPattern.basic", "PAMI.partialPeriodicPattern", "PAMI.partialPeriodicPattern.basic", "PAMI.partialPeriodicPattern.closed", "PAMI.partialPeriodicPattern.maximal", "PAMI.partialPeriodicPattern.pyspark", "PAMI.partialPeriodicPattern.topk", "PAMI.partialPeriodicPatternInMultipleTimeSeries", "PAMI.periodicCorrelatedPattern", "PAMI.periodicCorrelatedPattern.basic", "PAMI.periodicFrequentPattern", "PAMI.periodicFrequentPattern.basic", "PAMI.periodicFrequentPattern.closed", "PAMI.periodicFrequentPattern.cuda", "PAMI.periodicFrequentPattern.maximal", "PAMI.periodicFrequentPattern.pyspark", "PAMI.periodicFrequentPattern.topk", "PAMI.periodicFrequentPattern.topk.TopkPFP", "PAMI.periodicFrequentPattern.topk.kPFPMiner", "PAMI.recurringPattern", "PAMI.recurringPattern.basic", "PAMI.relativeFrequentPattern", "PAMI.relativeFrequentPattern.basic", "PAMI.relativeHighUtilityPattern", "PAMI.relativeHighUtilityPattern.basic", "PAMI.sequence", "PAMI.sequentialPatternMining", "PAMI.sequentialPatternMining.basic", "PAMI.sequentialPatternMining.closed", "PAMI.stablePeriodicFrequentPattern", "PAMI.stablePeriodicFrequentPattern.basic", "PAMI.stablePeriodicFrequentPattern.topK", "PAMI.subgraphMining", "PAMI.subgraphMining.basic", "PAMI.subgraphMining.topK", "PAMI.uncertainFaultTolerantFrequentPattern", "PAMI.uncertainFrequentPattern", "PAMI.uncertainFrequentPattern.basic", "PAMI.uncertainGeoreferencedFrequentPattern", "PAMI.uncertainGeoreferencedFrequentPattern.basic", "PAMI.uncertainPeriodicFrequentPattern", "PAMI.uncertainPeriodicFrequentPattern.basic", "PAMI.weightedFrequentNeighbourhoodPattern", "PAMI.weightedFrequentNeighbourhoodPattern.basic", "PAMI.weightedFrequentPattern", "PAMI.weightedFrequentPattern.basic", "PAMI.weightedFrequentRegularPattern", "PAMI.weightedFrequentRegularPattern.basic", "PAMI.weightedUncertainFrequentPattern", "PAMI.weightedUncertainFrequentPattern.basic", "PartialPeriodicFrequentPatternMining1", "PartialPeriodicPatternMining1", "PeriodicCorrelatedPatternMining1", "PeriodicFrequentPatternMining1", "RecurringPatternMining1", "RelativeHighUtilityPatternMining1", "SequentialFrequentPatternMining1", "StablePeriodicPatternMining1", "UncertainFrequentPatternMining1", "UncertainGeoReferencedFrequentPatternMining1", "UncertainPeriodicFrequentPatternMining1", "WeightedFrequentNeighbourhoodPatternMining1", "WeightedFrequentPatternMining1", "WeightedFrequentRegularPatternMining1", "contiguousFrequentPatterns", "contiguousPatternMining", "correlatedPatternBasicCoMine", "correlatedPatternBasicCoMinePlus", "correlatedPatternMining", "coveragePatternBasicCMine", "coveragePatternBasicCPPG", "coveragePatternMining", "faultTolerantFrequentPatternBasicFTApriori", "faultTolerantFrequentPatternBasicFTFPGrowth", "faultTolerantPatternMining", "frequent1", "frequentPatternBasicApriori", "frequentPatternBasicAprioribitset", "frequentPatternBasicECLAT", "frequentPatternBasicECLATDiffset", "frequentPatternBasicECLATbitset", "frequentPatternBasicFPGrowth", "frequentPatternCUDAcuApriori", "frequentPatternCUDAcuAprioriBit", "frequentPatternCUDAcuAprioriGCT", "frequentPatternCUDAcuAprioriTID", "frequentPatternCUDAcuECLAT", "frequentPatternCUDAcuECLATBit", "frequentPatternCUDAcuECLATGCT", "frequentPatternMaximalmaxFPGrowth", "frequentPatternMining", "frequentPatternPysparkParallelApriori", "frequentPatternPysparkParallelECLAT", "frequentPatternPysparkParallelFPGrowth", "frequentPatternTopkFAE", "frequentPatternWithMultipleMinimumSupport", "frequentPatternclosedCHARM", "fuzzyCorrelatedPatternMining", "fuzzyCorrelatedPatternbasicFCPGrowth", "fuzzyFrequentPatternMining", "fuzzyFrequentPatternbasicFFIMiner", "fuzzyGeoReferencedFrequentPatternMining", "fuzzyGeoReferencedPeriodicFrequentPatternMining", 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"periodicCorrelatedPatternbasicEPCPGrowth", "periodicFrequentPatternMining", "periodicFrequentPatternbasicPFECLAT", "periodicFrequentPatternbasicPFPGrowth", "periodicFrequentPatternbasicPFPGrowthPlus", "periodicFrequentPatternbasicPFPMC", "periodicFrequentPatternbasicPSGrowth", "periodicFrequentPatternclosedCPFPMiner", "periodicFrequentPatternmaximalMaxPFGrowth", "periodicFrequentPatterntopkTopkPFPTopkPFP", "periodicFrequentPatterntopkkPFPMinerkPFPMiner", "recurringPatternMining", "recurringPatternbasicRPGrowth", "relativeFrequent", "relativeFrequentPattern", "relativeFrequentPatternBasicRSFPGrowth", "relativeHighUtilityPatternBasicRHUIM", "relativeHighUtilityPatternMining", "sequentialFrequentPatternMining", "sequentialPatternMining", "sequentialPatternMiningBasicSPADE", "sequentialPatternMiningBasicSPAM", "sequentialPatternMiningBasicprefixSpan", "sequentialPatternMiningClosedbide", "stablePeriodicFrequentPatternbasicSPPEclat", "stablePeriodicFrequentPatternbasicSPPGrowth", 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"localPeriodicPatternbasicLPPMBreadth.rst", "localPeriodicPatternbasicLPPMDepth.rst", "modules.rst", "multipleMinimumSupportBasedFrequentPatternBasicCFPGrowth.rst", "multipleMinimumSupportBasedFrequentPatternBasicCFPGrowthPlus.rst", "multiplePartialPeriodicPatternMining.rst", "multipleTimeseriesPatternMining.rst", "partialPeriodicFrequentPatternMining.rst", "partialPeriodicFrequentPatternbasicGPFgrowth.rst", "partialPeriodicFrequentPatternbasicPPF_DFS.rst", "partialPeriodicPatternInMultipleTimeSeriesPPGrowth.rst", "partialPeriodicPatternMining.rst", "partialPeriodicPatternbasicGThreePGrowth.rst", "partialPeriodicPatternbasicPPPGrowth.rst", "partialPeriodicPatternbasicPPP_ECLAT.rst", "partialPeriodicPatternclosedPPPClose.rst", "partialPeriodicPatternmaximalMax3PGrowth.rst", "partialPeriodicPatterntopkk3PMiner.rst", "periodicCorrelatedPatternMining.rst", "periodicCorrelatedPatternbasicEPCPGrowth.rst", "periodicFrequentPatternMining.rst", "periodicFrequentPatternbasicPFECLAT.rst", "periodicFrequentPatternbasicPFPGrowth.rst", "periodicFrequentPatternbasicPFPGrowthPlus.rst", "periodicFrequentPatternbasicPFPMC.rst", "periodicFrequentPatternbasicPSGrowth.rst", "periodicFrequentPatternclosedCPFPMiner.rst", "periodicFrequentPatternmaximalMaxPFGrowth.rst", "periodicFrequentPatterntopkTopkPFPTopkPFP.rst", "periodicFrequentPatterntopkkPFPMinerkPFPMiner.rst", "recurringPatternMining.rst", "recurringPatternbasicRPGrowth.rst", "relativeFrequent.rst", "relativeFrequentPattern.rst", "relativeFrequentPatternBasicRSFPGrowth.rst", "relativeHighUtilityPatternBasicRHUIM.rst", "relativeHighUtilityPatternMining.rst", "sequentialFrequentPatternMining.rst", "sequentialPatternMining.rst", "sequentialPatternMiningBasicSPADE.rst", "sequentialPatternMiningBasicSPAM.rst", "sequentialPatternMiningBasicprefixSpan.rst", "sequentialPatternMiningClosedbide.rst", "stablePeriodicFrequentPatternbasicSPPEclat.rst", "stablePeriodicFrequentPatternbasicSPPGrowth.rst", "stablePeriodicFrequentPatterntopKTSPIN.rst", "stablePeriodicPatternMining.rst", "temporalPatternMining.rst", "transactionalPatternMining.rst", "uncertainFrequentPatternBasicCUFPTree.rst", "uncertainFrequentPatternBasicPUFGrowth.rst", "uncertainFrequentPatternBasicTUFP.rst", "uncertainFrequentPatternBasicTubeP.rst", "uncertainFrequentPatternBasicTubeS.rst", "uncertainFrequentPatternBasicUFGrowth.rst", "uncertainFrequentPatternBasicUVECLAT.rst", "uncertainFrequentPatternMining.rst", "uncertainGeoReferencedFrequentPatternMining.rst", "uncertainGeoreferencedFrequentPatternBasicGFPGrowth.rst", "uncertainPatternMining.rst", "uncertainPeriodicFrequentPatternBasicUPFPGrowth.rst", "uncertainPeriodicFrequentPatternBasicUPFPGrowthPlus.rst", "uncertainPeriodicFrequentPatternMining.rst", "utilityPatternMining.rst", "weightedFrequentNeighbourhoodPatternBasicSWFPGrowth.rst", "weightedFrequentNeighbourhoodPatternMining.rst", "weightedFrequentPatternBasicWFIM.rst", "weightedFrequentPatternMining.rst", "weightedFrequentRegularPatternBasicWFRIMiner.rst", "weightedFrequentRegularPatternMining.rst"], "titles": ["Contiguous Frequent Patterns", "Correlated Pattern Mining", "Coverage Pattern Mining", "Fault-Tolerant Frequent Pattern Mining", "Frequent pattern With Multiple Minimum Support", "Fuzzy Correlated Pattern Mining", "Fuzzy Frequent Pattern Mining", "Fuzzy Geo-referenced Frequent Pattern Mining", "Fuzzy Geo-referenced Periodic Frequent Pattern Mining", "Fuzzy Periodic Frequent Pattern Mining", "Geo-referenced Frequent Pattern Mining", "Geo-referenced Frequent Sequence Pattern mining", "Geo-referenced Partial Periodic Pattern Mining", "Geo-referenced Periodic Frequent Pattern Mining", "High-Utility Frequent Pattern Mining", "High-Utility Geo-referenced Frequent Pattern Mining", "High-Utility Pattern mining", "High-Utility Spatial Pattern Mining", "Local Periodic Pattern Mining", "Multiple Partial Periodic Pattern Mining", "PAMI package", "PAMI.AssociationRules package", "PAMI.AssociationRules.basic package", "PAMI.correlatedPattern package", "PAMI.correlatedPattern.basic package", "PAMI.coveragePattern package", "PAMI.coveragePattern.basic package", "PAMI.extras package", "PAMI.extras.DF2DB package", "PAMI.extras.calculateMISValues package", "PAMI.extras.dbStats package", "PAMI.extras.fuzzyTransformation package", "PAMI.extras.generateDatabase package", "PAMI.extras.graph package", "PAMI.extras.image2Database package", "PAMI.extras.imageProcessing package", "PAMI.extras.messaging package", "PAMI.extras.neighbours package", "PAMI.extras.sampleDatasets package", "PAMI.extras.stats package", "PAMI.extras.syntheticDataGenerator package", "PAMI.extras.visualize package", "PAMI.faultTolerantFrequentPattern package", "PAMI.faultTolerantFrequentPattern.basic package", "PAMI.frequentPattern package", "PAMI.frequentPattern.basic package", "PAMI.frequentPattern.closed package", "PAMI.frequentPattern.cuda package", "PAMI.frequentPattern.maximal package", "PAMI.frequentPattern.pyspark package", "PAMI.frequentPattern.topk package", "PAMI.fuzzyCorrelatedPattern package", "PAMI.fuzzyCorrelatedPattern.basic package", "PAMI.fuzzyFrequentPattern package", "PAMI.fuzzyFrequentPattern.basic package", "PAMI.fuzzyGeoreferencedFrequentPattern package", "PAMI.fuzzyGeoreferencedFrequentPattern.basic package", "PAMI.fuzzyGeoreferencedPeriodicFrequentPattern package", "PAMI.fuzzyGeoreferencedPeriodicFrequentPattern.basic package", "PAMI.fuzzyPartialPeriodicPatterns package", "PAMI.fuzzyPartialPeriodicPatterns.basic package", "PAMI.fuzzyPeriodicFrequentPattern package", "PAMI.fuzzyPeriodicFrequentPattern.basic package", "PAMI.geoReferencedPeriodicFrequentPattern package", "PAMI.geoReferencedPeriodicFrequentPattern.basic package", "PAMI.georeferencedFrequentPattern package", "PAMI.georeferencedFrequentPattern.basic package", "PAMI.georeferencedFrequentSequencePattern package", "PAMI.georeferencedPartialPeriodicPattern package", "PAMI.georeferencedPartialPeriodicPattern.basic package", "PAMI.highUtilityFrequentPattern package", "PAMI.highUtilityFrequentPattern.basic package", "PAMI.highUtilityGeoreferencedFrequentPattern package", "PAMI.highUtilityGeoreferencedFrequentPattern.basic package", "PAMI.highUtilityPattern package", "PAMI.highUtilityPattern.basic package", "PAMI.highUtilityPattern.parallel package", "PAMI.highUtilityPatternsInStreams package", "PAMI.highUtilitySpatialPattern package", "PAMI.highUtilitySpatialPattern.basic package", "PAMI.highUtilitySpatialPattern.topk package", "PAMI.localPeriodicPattern package", "PAMI.localPeriodicPattern.basic package", "PAMI.multipleMinimumSupportBasedFrequentPattern package", "PAMI.multipleMinimumSupportBasedFrequentPattern.basic package", "PAMI.partialPeriodicFrequentPattern package", "PAMI.partialPeriodicFrequentPattern.basic package", "PAMI.partialPeriodicPattern package", "PAMI.partialPeriodicPattern.basic package", "PAMI.partialPeriodicPattern.closed package", "PAMI.partialPeriodicPattern.maximal package", "PAMI.partialPeriodicPattern.pyspark package", "PAMI.partialPeriodicPattern.topk package", "PAMI.partialPeriodicPatternInMultipleTimeSeries package", "PAMI.periodicCorrelatedPattern package", "PAMI.periodicCorrelatedPattern.basic package", "PAMI.periodicFrequentPattern package", "PAMI.periodicFrequentPattern.basic package", "PAMI.periodicFrequentPattern.closed package", "PAMI.periodicFrequentPattern.cuda package", "PAMI.periodicFrequentPattern.maximal package", "PAMI.periodicFrequentPattern.pyspark package", "PAMI.periodicFrequentPattern.topk package", "PAMI.periodicFrequentPattern.topk.TopkPFP package", "PAMI.periodicFrequentPattern.topk.kPFPMiner package", "PAMI.recurringPattern package", "PAMI.recurringPattern.basic package", "PAMI.relativeFrequentPattern package", "PAMI.relativeFrequentPattern.basic package", "PAMI.relativeHighUtilityPattern package", "PAMI.relativeHighUtilityPattern.basic package", "PAMI.sequence package", "PAMI.sequentialPatternMining package", "PAMI.sequentialPatternMining.basic package", "PAMI.sequentialPatternMining.closed package", "PAMI.stablePeriodicFrequentPattern package", "PAMI.stablePeriodicFrequentPattern.basic package", "PAMI.stablePeriodicFrequentPattern.topK package", "PAMI.subgraphMining package", "PAMI.subgraphMining.basic package", "PAMI.subgraphMining.topK package", "PAMI.uncertainFaultTolerantFrequentPattern package", "PAMI.uncertainFrequentPattern package", "PAMI.uncertainFrequentPattern.basic package", "PAMI.uncertainGeoreferencedFrequentPattern package", "PAMI.uncertainGeoreferencedFrequentPattern.basic package", "PAMI.uncertainPeriodicFrequentPattern package", "PAMI.uncertainPeriodicFrequentPattern.basic package", "PAMI.weightedFrequentNeighbourhoodPattern package", "PAMI.weightedFrequentNeighbourhoodPattern.basic package", "PAMI.weightedFrequentPattern package", "PAMI.weightedFrequentPattern.basic package", "PAMI.weightedFrequentRegularPattern package", "PAMI.weightedFrequentRegularPattern.basic package", "PAMI.weightedUncertainFrequentPattern package", "PAMI.weightedUncertainFrequentPattern.basic package", "Partial Periodic Frequent Pattern Mining", "Partial Periodic Pattern Mining", "Periodic correlated pattern mining", "Periodic Frequent Pattern Mining", "Recurring Pattern Mining", "Relative High-Utility Pattern Mining", "Sequential Frequent Pattern mining", "Stable Periodic Pattern Mining", "Uncertain Frequent Pattern mining", "Uncertain Geo-Referenced Frequent Pattern mining", "Uncertain Periodic Frequent Pattern mining", "Weighted Frequent Neighbourhood Pattern Mining", "Weighted Frequent Pattern Mining", "Weighted Frequent Regular Pattern Mining", "<no title>", "Contiguous Patterns", "CoMine", "CoMinePlus", "Basic", "CMine", "CPPG", "Basic", "FTApriori", "FTFPGrowth", "Basic", "Frequent Pattern mining", "Apriori", "Aprioribitset", "ECLAT", "ECLATDiffset", "ECLATbitset", "FPGrowth", "cuApriori", "cuAprioriBit", "cudaAprioriGCT", "cudaAprioriTID", "cuEclat", "cuEclatBit", "cudaEclatGCT", "MaxFPGrowth", "Basic", "parallelApriori", "parallelECLAT", "parallelFPGrowth", "FAE", "Basic", "CHARM", "Basic", "FCPGrowth", "Basic", "FFIMiner", "Basic", "Basic", "FFSPMiner", "FGPFPMiner", "Fuzzy Pattern Mining", "Basic", "FPFPMiner", "Basic", "<no title>", "Basic", "Geo-referenced Pattern Mining", "Basic", "GPFPMiner", "FSPGrowth", "SpatialECLAT", "STEclat", "HUFIM", "Basic", "Basic", "SHUFIM", "EFIM", "HMiner", "UPGrowth", "Basic", "HDSHUIM", "SHUIM", "Basic", "TKSHUIM", "Welcome to PAMI\u2019s documentation!", "Basic", "LPPGrowth", "LPPMBreadth", "LPPMDepth", "PAMI", "CFPGrowth", "CFPGrowthPlus", "Basic", "Multiple Timeseries", "Basic", "GPFgrowth", "PPF_DFS", "PPGrowth", "Basic", "GThreePGrowth", "PPPGrowth", "PPP_ECLAT", "PPPClose", "Max3PGrowth", "k3PMiner", "Basic", "EPCPGrowth", "Basic", "PFECLAT", "PFPGrowth", "PFPGrowthPlus", "PFPMC", "PSGrowth", "CPFPMiner", "MaxPFGrowth", "TopkPFP", "kPFPMiner", "Basic", 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198, 199, 201, 202, 203, 206, 215, 256, 275, 276, 277, 281], "spatial": [3, 7, 8, 10, 11, 12, 13, 15, 52, 54, 56, 58, 60, 62, 66, 69, 73, 75, 79, 80, 129, 147, 160, 184, 186, 187, 188, 189, 190, 191, 193, 194, 195, 196, 197, 198, 201, 202, 205, 206, 209, 211, 212, 213, 214, 215, 277, 281, 282, 283], "remot": [3, 160], "sens": [3, 160], "imag": [3, 160], "weather": [3, 160], "forecast": [3, 5, 18, 139, 140, 146, 160, 183, 216, 238, 248, 280], "refer": [4, 7, 9, 24, 26, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 121, 123, 125, 127, 129, 131, 133, 135, 140, 145, 147, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 181, 182, 184, 186, 187, 189, 190, 192, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 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265, 266, 267, 268, 269, 270, 271, 273, 276, 277, 278, 279, 281, 282, 284, 286], "singl": [4, 45, 71, 75, 80, 110, 119, 120, 166, 181, 203, 207, 214, 253], "uniform": [4, 181, 265], "all": [4, 24, 26, 28, 30, 35, 39, 49, 54, 56, 58, 60, 62, 71, 73, 75, 78, 79, 80, 82, 84, 86, 89, 90, 91, 92, 106, 108, 110, 116, 119, 120, 127, 152, 153, 155, 177, 179, 181, 186, 189, 190, 191, 193, 203, 206, 207, 208, 211, 212, 214, 217, 221, 222, 233, 234, 249, 250, 251, 252, 253, 261, 262, 265, 266, 277, 279], "vari": [4, 18, 136, 143, 145, 181, 216, 225, 264, 275, 281], "level": [4, 33, 101, 181], "By": [4, 45, 162, 181], "more": [4, 18, 66, 143, 181, 201, 216, 264, 265], "nuanc": [4, 181], "each": [4, 12, 14, 17, 19, 30, 39, 49, 73, 75, 79, 80, 82, 119, 120, 139, 141, 145, 146, 177, 178, 179, 181, 191, 196, 204, 206, 209, 211, 212, 213, 214, 217, 218, 219, 223, 238, 250, 251, 254, 256, 265, 266, 275, 277, 280, 281], "evalu": [4, 181], "individu": [4, 181, 191, 277, 281], "its": [4, 17, 29, 30, 39, 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17, 19, 79, 137, 139, 141, 142, 144, 145, 146, 147, 148, 149, 183, 187, 188, 192, 194, 195, 204, 205, 211, 213, 223, 229, 238, 254, 255, 274, 275, 280, 283, 285, 287], "explor": [5, 71, 110, 119, 183, 203, 253], "itemset": [5, 24, 45, 46, 48, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 86, 88, 91, 101, 110, 123, 129, 131, 133, 135, 141, 149, 152, 153, 166, 175, 182, 183, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 227, 230, 231, 253, 254, 256, 271, 273, 282, 284, 286, 287], "exhibit": [5, 7, 8, 9, 12, 136, 137, 138, 139, 143, 147, 149, 183, 187, 188, 192, 196, 225, 229, 236, 238, 264, 283, 287], "linear": [5, 183], "assess": [5, 183], "through": [5, 119, 123, 183, 271], "instead": [5, 183], "sole": [5, 138, 183, 236], "co": [5, 183], "strength": [5, 183], "uncov": [5, 183], "basket": [5, 14, 91, 101, 141, 148, 183, 204, 250, 251, 254, 285], "analyt": [5, 14, 104, 148, 149, 183, 204, 247, 285, 287], "financi": [5, 6, 9, 137, 140, 141, 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164, 165, 166, 167, 175, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 192, 193, 194, 195, 196, 198, 199, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 252, 253, 254, 255, 256, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 273, 274, 275, 276, 277, 278, 279, 280, 282, 283, 284, 285, 286, 287], "python": [20, 24, 26, 45, 46, 50, 54, 56, 58, 86, 88, 92, 97, 98, 101, 103, 116, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 162, 163, 164, 165, 166, 167, 180, 182, 186, 189, 190, 226, 227, 232, 235, 239, 240, 244, 246, 261, 267, 268, 269, 270, 271, 276, 278, 279, 282, 284, 286], "librari": 20, "class": [24, 26, 27, 28, 29, 30, 31, 32, 33, 35, 36, 37, 39, 40, 41, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "ifil": [24, 26, 27, 29, 30, 31, 33, 37, 39, 41, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "union": [24, 28, 30, 39, 43, 62, 71, 82, 88, 100, 101, 108, 129, 152, 153, 159, 193, 203, 218, 219, 230, 245, 252, 282], "str": [24, 26, 27, 28, 29, 30, 31, 32, 33, 35, 36, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "datafram": [24, 26, 27, 28, 29, 30, 32, 33, 35, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "minsup": [24, 26, 33, 43, 45, 46, 48, 49, 52, 54, 56, 58, 60, 62, 64, 66, 71, 73, 75, 79, 84, 86, 93, 95, 97, 98, 100, 101, 103, 108, 110, 116, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 139, 152, 153, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 182, 184, 186, 189, 190, 193, 199, 201, 203, 206, 208, 211, 212, 221, 222, 226, 227, 228, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 252, 253, 261, 262, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "int": [24, 26, 27, 28, 29, 30, 32, 33, 35, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "float": [24, 26, 27, 28, 30, 32, 35, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "minallconf": [24, 52, 95, 152, 153, 184, 237], "sep": [24, 26, 27, 29, 30, 31, 32, 35, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 191, 193, 197, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 224, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 256, 261, 262, 263, 265, 266, 267, 268, 269, 270, 271, 273, 276, 277, 278, 279, 281, 282, 284, 286], "t": [24, 26, 27, 30, 31, 32, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 191, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 277, 278, 279, 281, 282, 284, 286], "sourc": [24, 26, 27, 28, 29, 30, 31, 32, 33, 35, 36, 37, 39, 40, 41, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "_correlatedpattern": [24, 152, 153], "about": [24, 26, 30, 39, 45, 46, 50, 54, 86, 97, 119, 152, 153, 155, 162, 163, 164, 165, 166, 167, 180, 182, 186, 226, 227, 239, 240], "algorithm": [24, 26, 33, 43, 45, 46, 48, 49, 50, 52, 54, 60, 64, 66, 69, 71, 75, 76, 78, 79, 80, 82, 84, 86, 89, 90, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 199, 201, 202, 203, 207, 208, 209, 211, 212, 217, 218, 219, 221, 222, 226, 227, 228, 233, 234, 235, 237, 239, 240, 241, 243, 244, 245, 246, 247, 249, 252, 253, 263, 265, 266, 267, 268, 269, 270, 271, 273, 276, 277, 279, 282, 284, 286], "descript": [24, 26, 27, 28, 29, 30, 31, 32, 33, 35, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 281, 282, 284, 286], "fundament": [24, 43, 45, 48, 49, 69, 84, 88, 91, 93, 97, 100, 101, 106, 121, 123, 131, 133, 152, 153, 158, 159, 162, 163, 164, 166, 167, 175, 179, 202, 221, 228, 230, 231, 232, 239, 240, 241, 242, 243, 245, 249, 267, 268, 269, 270, 273, 284, 286], "correl": [24, 52, 54, 86, 95, 152, 153, 154, 183, 184, 186, 191, 215, 226, 227, 236, 237, 265, 266], "fp": [24, 28, 43, 45, 49, 131, 152, 153, 159, 167, 179, 284], "growth": [24, 48, 49, 75, 82, 90, 97, 100, 127, 152, 153, 175, 179, 209, 217, 234, 243, 245, 279], "depth": [24, 46, 54, 82, 89, 98, 119, 152, 153, 182, 186, 217, 218, 219, 233, 244], "first": [24, 45, 46, 49, 54, 75, 80, 82, 89, 98, 110, 119, 120, 152, 153, 162, 179, 182, 186, 207, 214, 217, 218, 219, 224, 233, 244, 253, 265, 277], "search": [24, 43, 45, 46, 49, 54, 56, 58, 62, 75, 76, 82, 84, 89, 98, 119, 121, 131, 133, 152, 153, 158, 159, 162, 167, 177, 178, 179, 182, 186, 189, 190, 193, 215, 217, 218, 219, 222, 233, 244, 284, 286], "lee": [24, 97, 127, 152, 153, 240, 278], "y": [24, 33, 43, 45, 71, 97, 104, 116, 117, 119, 120, 152, 153, 159, 167, 203, 239, 247, 262, 263], "kim": [24, 152, 153], "w": [24, 79, 116, 127, 152, 153, 212, 261, 278], "cao": [24, 152, 153], "d": [24, 152, 153, 256, 265, 266], "han": [24, 43, 45, 84, 152, 153, 158, 159, 167, 221], "j": [24, 43, 45, 46, 48, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 91, 97, 110, 116, 119, 120, 123, 127, 131, 152, 153, 159, 167, 175, 182, 203, 206, 207, 212, 214, 217, 218, 219, 221, 226, 232, 233, 241, 253, 261, 267, 278, 284], "2003": [24, 45, 152, 153, 165], "icdm": [24, 123, 152, 153, 271], "pp": [24, 45, 49, 56, 62, 69, 79, 80, 93, 97, 110, 116, 129, 131, 133, 152, 153, 162, 177, 189, 193, 202, 211, 214, 228, 243, 253, 261, 282, 284, 286], "581": [24, 152, 153], "584": [24, 152, 153], "paramet": [24, 26, 27, 28, 29, 31, 32, 33, 35, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "name": [24, 26, 27, 28, 29, 30, 31, 32, 33, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 277, 278, 279, 282, 284, 286], "input": [24, 26, 27, 29, 30, 31, 32, 33, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "file": [24, 26, 27, 28, 29, 30, 31, 32, 33, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "complet": [24, 26, 28, 29, 30, 31, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 136, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 225, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 277, 278, 279, 282, 284, 286], "ofil": [24, 26, 27, 28, 29, 30, 31, 35, 37, 39, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "output": [24, 26, 27, 28, 29, 30, 31, 32, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 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43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "start": [24, 26, 33, 43, 45, 46, 48, 49, 50, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 224, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 265, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "endtim": [24, 26, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "given": [24, 27, 28, 29, 32, 33, 40, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 86, 90, 108, 110, 119, 120, 152, 153, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 226, 227, 234, 250, 251, 252, 253], "minimum": [24, 26, 27, 29, 30, 39, 43, 50, 54, 56, 58, 60, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 97, 98, 100, 101, 106, 108, 110, 116, 119, 120, 121, 123, 125, 127, 129, 131, 135, 139, 152, 153, 155, 156, 158, 180, 181, 189, 190, 206, 209, 211, 212, 214, 215, 217, 218, 219, 221, 222, 230, 231, 232, 233, 234, 235, 238, 241, 242, 243, 244, 245, 249, 252, 253, 261, 262, 266, 267, 276, 278, 279, 282, 284], "ratio": [24, 52, 136, 152, 153, 184, 225], "should": [24, 52, 119, 152, 153, 184], "list": [24, 26, 27, 28, 30, 32, 35, 39, 40, 43, 45, 46, 48, 49, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 88, 90, 91, 92, 93, 95, 97, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 179, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 221, 222, 228, 230, 231, 232, 234, 235, 237, 239, 240, 241, 242, 243, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "mapsupport": [24, 43, 45, 46, 48, 84, 88, 90, 91, 93, 95, 97, 100, 101, 106, 108, 116, 117, 123, 125, 127, 129, 131, 133, 135, 152, 153, 159, 167, 175, 182, 221, 222, 228, 230, 231, 232, 234, 237, 239, 240, 241, 242, 243, 245, 249, 252, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "dictionari": [24, 26, 27, 30, 31, 39, 43, 45, 46, 48, 49, 50, 54, 64, 66, 69, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 186, 199, 201, 202, 206, 212, 214, 217, 221, 222, 226, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "maintain": [24, 43, 45, 46, 48, 49, 82, 84, 88, 90, 91, 93, 95, 97, 100, 101, 106, 108, 116, 117, 123, 125, 127, 129, 131, 133, 135, 152, 153, 159, 167, 175, 179, 182, 217, 221, 222, 228, 230, 231, 232, 234, 237, 239, 240, 241, 242, 243, 245, 249, 252, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "lno": [24, 43, 48, 49, 84, 88, 90, 91, 93, 95, 97, 100, 101, 104, 106, 108, 116, 117, 123, 125, 127, 129, 131, 133, 135, 152, 153, 159, 175, 177, 178, 179, 221, 222, 228, 230, 231, 232, 234, 237, 239, 240, 241, 242, 243, 245, 247, 249, 252, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 279, 282, 284, 286], "tree": [24, 43, 45, 46, 48, 49, 71, 73, 75, 79, 80, 82, 84, 88, 90, 91, 93, 95, 97, 100, 101, 106, 108, 110, 116, 117, 123, 125, 127, 129, 131, 133, 135, 152, 153, 159, 167, 175, 179, 182, 203, 206, 207, 209, 212, 214, 217, 221, 222, 228, 230, 231, 232, 234, 237, 239, 240, 241, 242, 243, 245, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "itemsetcount": [24, 46, 48, 90, 93, 95, 97, 100, 101, 106, 108, 116, 117, 123, 125, 127, 135, 152, 153, 175, 182, 228, 234, 237, 239, 240, 241, 242, 243, 245, 249, 252, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 279], "finalpattern": [24, 26, 31, 43, 45, 46, 48, 49, 50, 64, 66, 69, 78, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 199, 201, 202, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "dict": [24, 26, 27, 30, 31, 33, 39, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "itemsetbuff": [24, 54, 56, 58, 60, 62, 108, 152, 153, 186, 189, 190, 252], "maxpatternlength": [24, 108, 152, 153, 252], "constraint": [24, 73, 79, 101, 108, 110, 116, 139, 143, 152, 153, 206, 212, 238, 252, 253, 261, 262, 264], "length": [24, 27, 30, 32, 39, 40, 43, 75, 79, 82, 108, 121, 123, 125, 127, 135, 152, 153, 158, 208, 211, 217, 218, 219, 252, 267, 268, 269, 270, 271, 273, 276, 279], "execut": [24, 30, 39, 45, 46, 50, 54, 58, 80, 82, 86, 89, 91, 92, 97, 100, 101, 103, 106, 152, 153, 162, 163, 164, 165, 166, 167, 180, 182, 186, 190, 217, 218, 219, 226, 227, 233, 239, 240, 245, 246, 249], "method": [24, 26, 27, 30, 31, 32, 33, 37, 39, 40, 43, 45, 46, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 159, 162, 163, 164, 165, 166, 167, 177, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "termin": [24, 26, 45, 46, 50, 54, 56, 86, 93, 97, 98, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 162, 163, 164, 165, 166, 167, 180, 182, 186, 189, 226, 227, 228, 239, 240, 244, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "command": 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69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 91, 93, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 231, 232, 233, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "python3": [24, 26, 30, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "py": [24, 26, 30, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "inputfil": [24, 26, 27, 30, 39, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 90, 91, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "outputfil": [24, 26, 27, 28, 30, 32, 35, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 90, 91, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "exampl": [24, 26, 30, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 191, 193, 197, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 224, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 256, 261, 262, 263, 265, 266, 267, 268, 269, 270, 271, 273, 276, 277, 278, 279, 281, 282, 284, 286], "sampletdb": [24, 26, 48, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 86, 89, 90, 93, 95, 97, 98, 100, 101, 106, 110, 116, 117, 123, 125, 127, 135, 152, 153, 155, 156, 175, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 226, 227, 228, 233, 234, 237, 241, 242, 243, 244, 245, 249, 253, 261, 262, 263, 267, 276, 278, 279], "txt": [24, 26, 30, 32, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "25": [24, 54, 86, 152, 153, 186, 226, 227], "2": [24, 40, 48, 50, 52, 54, 56, 58, 60, 62, 69, 73, 79, 80, 88, 89, 91, 97, 98, 100, 106, 108, 116, 121, 127, 129, 152, 153, 175, 180, 184, 186, 189, 190, 191, 193, 197, 202, 206, 212, 214, 224, 230, 231, 233, 241, 242, 243, 244, 245, 249, 252, 261, 265, 266, 277, 278, 279, 281, 282], "call": 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43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "calcul": [24, 26, 29, 30, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 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262, 263, 267, 268, 269, 270, 271, 276, 278, 279], "build": [24, 49, 75, 152, 153, 179, 209], "ani": [24, 26, 82, 86, 97, 98, 100, 101, 103, 148, 152, 153, 155, 156, 217, 218, 219, 226, 227, 239, 240, 241, 242, 243, 244, 245, 246, 265, 285], "current": [24, 80, 152, 153, 214, 277], "being": [24, 152, 153, 265], "_node": [24, 152, 153], "save": [24, 26, 27, 28, 29, 30, 32, 33, 35, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 265, 266, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "outfil": [24, 26, 28, 29, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 193, 199, 201, 202, 203, 206, 207, 208, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 227, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 252, 253, 261, 262, 263, 267, 268, 269, 270, 271, 276, 278, 279, 282, 284, 286], "an": [24, 26, 28, 29, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 62, 64, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 92, 95, 97, 98, 108, 110, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 139, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 175, 177, 178, 179, 180, 182, 184, 186, 189, 190, 191, 193, 197, 199, 202, 203, 206, 207, 208, 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243, 244, 245, 247, 262, 263, 267, 269, 270, 271, 273, 276, 278, 279, 284], "doi": [26, 43, 45, 46, 49, 50, 52, 56, 62, 69, 71, 75, 76, 79, 80, 82, 84, 86, 88, 91, 92, 93, 97, 104, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 155, 159, 162, 165, 167, 177, 180, 182, 184, 189, 193, 202, 203, 207, 209, 211, 214, 217, 218, 219, 221, 222, 226, 228, 230, 231, 235, 240, 241, 243, 247, 253, 262, 263, 267, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "10": [26, 27, 37, 40, 43, 45, 46, 49, 50, 52, 54, 56, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 155, 156, 158, 159, 162, 163, 164, 165, 166, 167, 177, 178, 179, 180, 182, 184, 186, 189, 191, 193, 197, 199, 201, 202, 203, 206, 207, 209, 211, 212, 214, 217, 218, 219, 221, 222, 226, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 249, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 281, 282, 284, 286], "1145": [26, 45, 75, 84, 88, 91, 123, 155, 162, 165, 209, 222, 230, 231, 273], "1963192": [26, 155], "1963259": [26, 155], "everi": [26, 78, 80, 82, 86, 92, 97, 98, 100, 101, 108, 155, 156, 217, 241, 242, 243, 244, 245, 252, 265, 277, 281], "must": [26, 78, 80, 86, 92, 97, 98, 100, 101, 108, 110, 155, 156, 191, 224, 241, 242, 243, 244, 245, 252, 253, 265, 266, 277, 281], "least": [26, 108, 155, 156, 252], "maximum": [26, 30, 32, 39, 40, 62, 71, 73, 75, 76, 79, 80, 82, 86, 90, 97, 98, 100, 101, 103, 106, 110, 116, 117, 127, 129, 139, 155, 156, 193, 203, 206, 207, 209, 211, 212, 214, 217, 218, 219, 226, 227, 234, 238, 239, 240, 241, 242, 243, 244, 245, 246, 249, 253, 261, 262, 263, 278, 279, 282], "two": [26, 40, 71, 73, 75, 79, 80, 82, 86, 97, 98, 100, 101, 103, 110, 120, 155, 156, 203, 206, 207, 209, 212, 214, 217, 218, 219, 224, 226, 227, 239, 240, 241, 242, 243, 244, 245, 246, 253, 265, 277], "reappear": [26, 82, 86, 97, 98, 100, 101, 103, 155, 156, 217, 218, 219, 226, 227, 239, 240, 241, 242, 243, 244, 245, 246], "4": [26, 52, 58, 69, 82, 88, 89, 90, 93, 95, 97, 98, 100, 101, 106, 116, 117, 123, 127, 131, 155, 156, 184, 190, 191, 197, 202, 217, 218, 219, 224, 228, 232, 233, 234, 237, 241, 242, 243, 244, 245, 249, 261, 262, 263, 265, 267, 277, 278, 279, 281, 284], "7": [26, 86, 155, 156, 191, 226, 227, 265, 277, 281], "5": [26, 40, 64, 66, 69, 82, 91, 97, 101, 116, 123, 133, 155, 156, 191, 197, 199, 201, 202, 217, 218, 219, 224, 242, 261, 269, 270, 277, 281, 286], "p": [26, 40, 43, 45, 46, 48, 50, 52, 56, 64, 69, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 90, 92, 93, 95, 97, 98, 100, 101, 103, 104, 110, 116, 117, 121, 123, 125, 127, 129, 131, 133, 155, 156, 158, 159, 162, 167, 175, 180, 182, 184, 189, 199, 202, 203, 206, 207, 211, 212, 214, 217, 218, 219, 221, 222, 226, 228, 230, 231, 232, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 253, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "likhitha": [26, 40, 43, 45, 46, 48, 50, 60, 69, 84, 88, 89, 90, 92, 93, 95, 97, 98, 100, 103, 104, 116, 117, 121, 123, 125, 127, 129, 131, 133, 155, 156, 158, 159, 162, 167, 175, 180, 182, 202, 221, 222, 228, 230, 231, 233, 234, 235, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 261, 262, 263, 267, 268, 269, 270, 271, 273, 276, 278, 279, 282, 284, 286], "creatingcoverageitem": [26, 155], "creat": [26, 28, 29, 32, 35, 37, 40, 49, 75, 79, 80, 82, 119, 120, 155, 179, 191, 197, 208, 211, 214, 217, 218, 219, 224, 256, 265, 266, 277, 281], "_databas": [26, 54, 155, 186], "coveragetiddata": [26, 155], "tid": [26, 32, 40, 52, 54, 56, 58, 60, 62, 82, 91, 101, 104, 155, 184, 186, 189, 190, 191, 193, 197, 217, 247, 265, 266, 277, 281], "genpattern": [26, 155], "prefix": [26, 46, 49, 52, 54, 56, 58, 60, 62, 75, 79, 80, 82, 86, 88, 91, 97, 108, 116, 155, 179, 182, 184, 186, 189, 190, 193, 208, 211, 214, 217, 227, 232, 239, 242, 252, 261], "tiddata": [26, 155], "gener": [26, 32, 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90, 98, 100, 163, 164, 166, 180, 234, 244, 245], "document": [45, 50, 90, 98, 100, 163, 164, 166, 180, 234, 244, 245], "846291": [45, 163, 164, 166], "kundai": [45, 58, 164, 165], "diffset": [45, 165], "kdd": [45, 75, 165, 209], "03": [45, 165], "proceed": [45, 46, 75, 88, 91, 123, 131, 165, 182, 209, 230, 231, 271, 273, 284], "ninth": [45, 165], "sigkdd": [45, 75, 165, 209], "intern": [45, 49, 54, 56, 62, 69, 75, 79, 80, 88, 91, 93, 98, 103, 110, 116, 123, 129, 131, 133, 165, 177, 186, 189, 193, 202, 209, 211, 214, 228, 230, 231, 244, 246, 253, 261, 271, 281, 282, 284, 286], "confer": [45, 49, 56, 62, 69, 75, 79, 80, 88, 91, 93, 98, 103, 110, 123, 129, 131, 133, 165, 177, 179, 189, 193, 202, 209, 211, 214, 228, 230, 231, 244, 246, 253, 268, 271, 282, 284, 286], "august": [45, 165], "page": [45, 86, 88, 91, 123, 165, 215, 226, 230, 231, 267, 273], "326": [45, 165], "335": [45, 165], "956750": [45, 165], "956788": [45, 165], "yudai": [45, 49, 163, 166, 177, 178, 179], "masu": [45, 49, 163, 166, 177, 178, 179], "implement": [45, 49, 86, 88, 97, 116, 166, 177, 227, 232, 239, 242, 261], "we": [45, 54, 56, 58, 62, 166, 186, 189, 190, 193, 250, 251, 266, 277], "check": [45, 46, 71, 73, 75, 79, 80, 90, 91, 97, 108, 110, 119, 120, 166, 182, 203, 206, 207, 212, 214, 234, 239, 241, 242, 252, 253], "superset": [46, 73, 182, 206], "same": [46, 49, 52, 54, 56, 58, 60, 62, 179, 182, 184, 186, 189, 190, 193, 197, 265], "origin": [46, 80, 120, 123, 125, 127, 135, 182, 214, 267, 268, 269, 270, 271, 273, 276, 278, 279], "ching": [46, 182], "jui": [46, 182], "hsiao": [46, 182], "2002": [46, 182], "siam": [46, 131, 182, 284], "sdm": [46, 182], "457": [46, 182], "473": [46, 182], "1137": [46, 131, 182, 284], "9781611972726": [46, 182], "27": [46, 182], "tidlist": [46, 66, 82, 88, 92, 97, 103, 104, 116, 182, 201, 217, 232, 235, 239, 242, 246, 247, 261], "hash": [46, 97, 182, 239, 242], "equival": [46, 64, 66, 86, 88, 97, 116, 123, 182, 199, 201, 227, 232, 239, 242, 261, 273], "maxfp": 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116, 121, 123, 127, 177, 209, 243, 247, 262, 271, 278, 279], "kyoto": [49, 177], "japan": [49, 177], "236": [49, 177], "241": [49, 177], "1109": [49, 50, 56, 62, 69, 79, 80, 93, 97, 110, 123, 129, 133, 177, 180, 189, 193, 202, 211, 214, 228, 243, 253, 271, 282, 286], "snpd": [49, 177], "31": [49, 177], "numpartit": [49, 91, 177, 178, 179], "partit": [49, 91, 101, 177, 178, 179], "On": [49, 177, 178, 179], "worker": [49, 101, 177, 178, 179], "executor": [49, 177, 178, 179], "unit": [49, 177, 178, 179], "children": [49, 82, 91, 97, 101, 179, 217, 243], "null": [49, 88, 90, 91, 93, 95, 97, 100, 101, 106, 110, 116, 117, 123, 125, 127, 135, 179, 228, 230, 231, 234, 237, 240, 241, 243, 245, 249, 253, 262, 263, 267, 268, 269, 270, 271, 276, 278, 279], "nodelink": [49, 82, 179, 217], "addtransact": [49, 82, 179, 217], "addnodetonodelink": [49, 179], "add": [49, 80, 82, 91, 101, 119, 120, 179, 214, 217], "generateconditionaltre": [49, 179], "haoyuan": [49, 179], "pfp": [49, 179], "queri": [49, 179], "recommend": [49, 106, 141, 179, 249, 254], "2008": [49, 179], "static": [49, 139, 179, 238], "buildtre": [49, 88, 90, 91, 93, 95, 97, 100, 101, 106, 116, 117, 123, 125, 127, 135, 179, 228, 230, 231, 234, 237, 240, 241, 243, 245, 249, 262, 263, 267, 268, 269, 270, 271, 276, 278, 279], "genallfrequentpattern": [49, 179], "tree_tupl": [49, 179], "id": [49, 52, 75, 76, 101, 119, 120, 179, 184], "gencondtransact": [49, 91, 101, 179], "genfreqpattern": [49, 179], "new": [49, 71, 73, 75, 79, 80, 84, 88, 89, 95, 106, 110, 119, 123, 179, 203, 206, 207, 209, 212, 214, 221, 232, 233, 237, 249, 253, 267], "getpartitionid": [49, 91, 101, 179], "zhi": [50, 180], "hong": [50, 54, 135, 180, 186], "deng": [50, 180], "guo": [50, 180], "dong": [50, 180], "fang": [50, 180], "icmlc": [50, 180], "2007": [50, 52, 180, 184], "4370261": [50, 180], "xplore": [50, 180], "topkfrequentpattern": [50, 180], "element": [52, 54, 56, 58, 60, 62, 66, 75, 79, 80, 119, 120, 141, 184, 186, 189, 190, 193, 201, 208, 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214], "region": [52, 54, 56, 58, 60, 62, 184, 189, 193], "mapitemsmidsum": [52, 54, 56, 60, 62, 184, 193], "middl": [52, 54, 56, 62, 184, 193], "mapitemshighsum": [52, 54, 56, 62, 184, 193], "mapitemsum": [52, 54, 56, 58, 60, 62, 184, 186, 189, 190, 193], "mapitemregion": [52, 54, 56, 58, 60, 62, 184, 189, 193], "jointcnt": [52, 54, 62, 184, 193], "ffi": [52, 54, 56, 58, 60, 62, 184, 186, 189, 190, 193], "construct": [52, 54, 56, 58, 60, 62, 75, 79, 88, 91, 97, 119, 120, 123, 125, 127, 135, 184, 186, 189, 190, 193, 208, 209, 211, 224, 230, 231, 241, 265, 266, 267, 268, 269, 270, 271, 273, 276, 278, 279], "buffers": [52, 54, 56, 58, 60, 62, 184, 186, 189, 190, 193], "buffer": [52, 54, 56, 58, 60, 62, 184, 186, 189, 190, 193], "itembuff": [52, 54, 62, 184, 193], "starttimemin": [52, 184], "getratio": [52, 184], "prefixlen": [52, 54, 56, 58, 60, 62, 75, 79, 184, 186, 189, 190, 193, 208, 211], "ration": [52, 184], "fsfimin": [52, 54, 56, 58, 62, 184, 186, 189, 190, 193], "fsfim": [52, 54, 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110, 116, 117, 127, 135, 186, 201, 203, 207, 217, 218, 219, 228, 253, 261, 262, 263, 279], "philipp": [54, 66, 89, 103, 127, 135, 186, 201, 233, 246, 279], "tzung": [54, 123, 135, 186, 267], "fast": [54, 75, 76, 123, 186, 207, 271], "29": [54, 186], "2373": [54, 186], "2379": [54, 186], "3233": [54, 186], "IFS": [54, 186], "151936": [54, 186], "researchg": [54, 186], "net": [54, 186], "286510908_a_fast_algorithm_for_mining_fuzzy_frequent_itemset": [54, 186], "joinscnt": [54, 56, 58, 60, 62, 186, 189, 190], "compareitem": [54, 60, 186], "o1": [54, 60, 186], "o2": [54, 60, 186], "ascend": [54, 60, 186], "cand": [54, 186], "doe": [54, 119, 186], "anyth": [54, 186], "explicitli": [54, 186], "updat": [54, 75, 79, 88, 90, 91, 93, 95, 97, 100, 101, 106, 116, 117, 119, 123, 125, 127, 135, 186, 208, 211, 228, 230, 231, 234, 237, 240, 241, 243, 245, 249, 262, 263, 267, 268, 269, 270, 271, 276, 278, 279], "_finalpattern": [54, 186], "fmfile": 54, "ffiminermin": 54, "fuzzymembership": 54, "nfile": 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66, 199, 201], "cluster": [64, 66, 199, 201], "bottom": [64, 66, 199, 201], "up": [64, 66, 75, 199, 201, 209], "lattic": [64, 66, 199, 201], "travers": [64, 66, 119, 199, 201], "referenc": [64, 66, 69, 71, 73, 125, 187, 188, 191, 194, 195, 196, 198, 199, 201, 202, 203, 206, 215, 256, 275, 276, 277, 281], "avail": [64, 66, 69, 199, 201, 202], "ifilenam": [64, 66, 69, 199, 201, 202], "getneighbouritem": [64, 66, 69, 199, 201, 202], "keyset": [64, 66, 69, 199, 201, 202], "mapneighbour": [64, 66, 69, 199, 201, 202], "neighbourfil": [64, 66, 69, 199, 201, 202], "georeferencedperidicfrequentpattern": [64, 199], "ravikumar": [64, 79, 88, 97, 104, 199, 212, 232, 239, 247], "_spatialfrequentpattern": [66, 201], "popular": [66, 201], "version": [66, 97, 201, 241], "koji": [66, 79, 90, 97, 100, 101, 125, 127, 201, 212, 234, 239, 245, 276, 279], "toyoda": [66, 69, 71, 86, 90, 100, 101, 106, 110, 127, 129, 201, 202, 203, 226, 234, 245, 249, 253, 279, 282], "masashi": [66, 86, 88, 89, 90, 100, 101, 106, 127, 201, 226, 232, 233, 234, 245, 249, 279], "kitsuregawa": [66, 69, 71, 86, 89, 90, 93, 100, 101, 106, 108, 129, 201, 202, 203, 226, 228, 233, 234, 245, 249, 252, 282], "masaru": [66, 86, 88, 89, 90, 100, 101, 106, 108, 201, 226, 232, 233, 234, 245, 249, 252], "veri": [66, 79, 80, 90, 97, 98, 100, 104, 110, 201, 211, 214, 234, 241, 244, 245, 247, 253], "dictkeystoint": [66, 201], "ilist": [66, 201], "eclatgener": [66, 92, 103, 104, 201, 235, 246, 247], "clist": [66, 201], "generatespatialfrequentpattern": [66, 201], "spatialfrequentpattern": [66, 201], "minp": [69, 88, 91, 92, 106, 108, 202, 230, 231, 232, 249, 252], "maxiat": [69, 202], "_partialperiodicspatialpattern": [69, 202], "georeferenec": [69, 202], "c": [69, 88, 93, 106, 116, 119, 120, 121, 129, 202, 224, 228, 232, 249, 256, 261, 265, 266, 282], "saideep": [69, 93, 101, 106, 202, 228, 249], "2019": [69, 71, 93, 116, 129, 202, 203, 228, 261, 282], "big": [69, 79, 80, 92, 98, 101, 104, 110, 116, 202, 211, 214, 235, 244, 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