www.gusucode.com > stats 源码程序 matlab案例代码 > stats/CreateDiscriminantAnalysisClassifiersExample.m
%% Create Discriminant Analysis Classifiers % This example shows how to train a basic discriminant analysis classifier % to classify irises in Fisher's iris data. %% % Load the data. load fisheriris %% % Create a default (linear) discriminant analysis classifier. MdlLinear = fitcdiscr(meas,species); %% % To visualize the classification boundaries of a 2-D linear classification % of the data, see <docid:stats_ug.brah8i8-1>. %% % Classify an iris with average measurements. meanmeas = mean(meas); meanclass = predict(MdlLinear,meanmeas) %% % Create a quadratic classifier. MdlQuadratic = fitcdiscr(meas,species,'DiscrimType','quadratic'); %% % To visualize the classification boundaries of a 2-D quadratic % classification of the data, see <docid:stats_ug.brah8i8-1>. %% % Classify an iris with average measurements using the quadratic % classifier. meanclass2 = predict(MdlQuadratic,meanmeas)