Version 0.2 (28 May 2016)

• Full Python3 support
• Update the parameters of the Logistic Regression Classifier manually. In literature, this is often denoted as the deterministic record linkage.
• Expectation/Conditional Maxisation algorithm completely rewritten. The performance of the algorithm is much better now. The algorithm is still experimental.
• New string comparison metrics: Q-gram string comparing and Cosine string comparing.
• New indexing algorithm: Q-gram indexing.
• Several internal tests.
• Updated documenation.
• BernoulliNBClassifier is now named NaiveBayesClassifier. No changes to the algorithm.
• Arguments order in compare functions corrected.
• Function to clean phone numbers
• Return the result of the classifier as index, numpy array or pandas series.
• Many bug fixes