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    %% Estimate the Resubstitution Edge of Naive Bayes Classifiers
%%
% Load Fisher's iris data set.

% Copyright 2015 The MathWorks, Inc.

load fisheriris
X = meas;    % Predictors
Y = species; % Response
rng(1);
%%
% Train a naive Bayes classifier. It is good practice to specify the class
% order. Assume that each predictor is conditionally, normally distributed
% given its label.
Mdl = fitcnb(X,Y,'ClassNames',{'setosa','versicolor','virginica'});
%%
% |Mdl| is a trained |ClassificationNaiveBayes| classifier.
%%
% Estimate the resubstitution edge. 
e = resubEdge(Mdl) 
%%
% The mean of the training sample margins is approximately |0.9|, which
% indicates that the classifier classifies in-sample observations with high
% confidence.