www.gusucode.com > stats 源码程序 matlab案例代码 > stats/EstimateInSampleClassificationMarginsOfECOCModelsExample.m
%% Estimate In-Sample Classification Margins of ECOC Models %% % Load Fisher's iris data set. % Copyright 2015 The MathWorks, Inc. load fisheriris X = meas; Y = species; %% % Train an ECOC model using SVM binary classifiers. It is good practice to % standardize the predictors and define the class order. Specify to % standardize the predictors using an SVM template. t = templateSVM('Standardize',1); classOrder = unique(Y) Mdl = fitcecoc(X,Y,'Learners',t,'ClassNames',classOrder); %% % |t| is an SVM template object. The software uses default values for empty % options in |t| during training. |Mdl| is a |ClassificationECOC| model. %% % Estimate the in-sample classification margins. Display the distribution % of the margins using a boxplot. m = resubMargin(Mdl); figure; boxplot(m); title 'In-Sample Margins' %% % An observation margin is the positive-class, negated loss minus the % maximum negative-class, negated loss. Classifiers that yield % relatively large margins are desirable.