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    %% Select SVM 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 the |ionosphere| data set. Define two data sets:
%
% * |fullX| contains all predictors (except the removed column of 0s).
% * |partX| contains the last 20 predictors.
%

% Copyright 2015 The MathWorks, Inc.

load ionosphere
fullX = X;
partX = X(:,end-20:end);
%%
% Train SVM classifiers for each predictor set.
FullSVMModel = fitcsvm(fullX,Y);
PartSVMModel = fitcsvm(partX,Y);
%%
% Estimate the training sample edge for each classifier.
fullEdge = resubEdge(FullSVMModel)
partEdge = resubEdge(PartSVMModel)
%%
% The edge for the classifier trained on the complete data set is greater,
% suggesting that the classifier trained using all of the predictors has a
% better in-sample fit.