Train_SleepStaging_RF.m

function [ss_rf,ss_rf_importance] = Train_SleepStaging_RF(n_trees,Sleep_table,SS_Features,hyp)
  % Copyright (c) 2018, Navin Cooray (University of Oxford)
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  %	Contact: navsnav@gmail.com
  %	Originally written by Navin Cooray 19-Sept-2018
% Input: (n_trees,Sleep,SS_Features,hyp)
%       n_trees: Number of trees to train random forest.
%       Sleep: Features/Data used to train rf model.
%       SS_Features: Specific features within Sleep used to train rf model.
%       hyp: Annotated sleep staging to train rf model. 
% Output:
%       ss_rf: Trained random forest model.   
%       ss_rf_importance: Feature importance values for each feature.

    ss_rf               = TreeBagger(n_trees,Sleep_table(:,SS_Features),hyp,'OOBPredictorImportance','on'); 
    ss_rf_importance    =  [ss_rf.OOBPermutedPredictorDeltaError',ss_rf.DeltaCriterionDecisionSplit'];

end