www.gusucode.com > stats 源码程序 matlab案例代码 > stats/CompareInSamplePosteriorProbabilitiesForEachSubTreeExample.m
%% Compare In-Sample Posterior Probabilities for Each Subtree %% % Load Fisher's iris data set. Partition the data into training (50%) % Copyright 2015 The MathWorks, Inc. load fisheriris %% % Grow a classification tree using the all petal measurements. Mdl = fitctree(meas(:,3:4),species); n = size(meas,1); % Sample size K = numel(Mdl.ClassNames); % Number of classes %% % View the classification tree. view(Mdl,'Mode','graph'); %% % The classification tree has four pruning levels. Level 0 is the full, % unpruned tree (as displayed). Level 4 is just the root node (i.e., no % splits). %% % Estimate the posterior probabilities for each class using the subtrees % pruned to levels 1 and 3. [~,Posterior] = resubPredict(Mdl,'SubTrees',[1 3]); %% % |Posterior| is an |n|-by- |K|-by- 2 array of % posterior probabilities. Rows of |Posterior| correspond to observations, % columns correspond to the classes with order |Mdl.ClassNames|, and pages % correspond to pruning level. %% % Display the class posterior probabilities for iris 125 using % each subtree. Posterior(125,:,:) %% % The decision stump (page 2 of |Posterior|) has trouble predicting whether % iris 125 is versicolor or virginica.