www.gusucode.com > stats 源码程序 matlab案例代码 > stats/PredictLabelsUsingAClassificationTreeExample.m
%% Predict Labels Using a Classification Tree % Examine predictions for a few rows in a data set left out of training. %% % Load Fisher's iris data set. % Copyright 2015 The MathWorks, Inc. load fisheriris %% % Partition the data into training (50%) and validation (50%) sets. n = size(meas,1); rng(1) % For reproducibility idxTrn = false(n,1); idxTrn(randsample(n,round(0.5*n))) = true; % Training set logical indices idxVal = idxTrn == false; % Validation set logical indices %% % Grow a classification tree using the training set. Mdl = fitctree(meas(idxTrn,:),species(idxTrn)); %% % Predict labels for the validation data. Count the number of % misclassified observations. label = predict(Mdl,meas(idxVal,:)); label(randsample(numel(label),5)) % Display several predicted labels numMisclass = sum(~strcmp(label,species(idxVal))) %% % The software misclassifies three out-of-sample observations.