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%% Select Naive Bayes Classifier Features by Comparing In-Sample Edges % The classifier edge measures the average of the classifier margins. One % way to perform feature selection is to compare training sample edges from % multiple models. Based solely on this criterion, the classifier with the % highest edge is the best classifier. %% % Load Fisher's iris data set. Define two data sets: % % * |fullX| contains all predictors. % * |partX| contains the last two predictors. % % Copyright 2015 The MathWorks, Inc. load fisheriris X = meas; % Predictors Y = species; % Response fullX = X; partX = X(:,3:4); %% % Train naive Bayes classifiers for each predictor set. FullMdl = fitcnb(fullX,Y); PartMdl = fitcnb(partX,Y); %% % Estimate the training sample edge for each classifier. fullEdge = resubEdge(FullMdl) partEdge = resubEdge(PartMdl) %% % The edge for the classifier trained on predictors 3 and 4 is greater, % suggesting that the classifier trained using only those predictors has a % better in-sample fit.