I investigated for finding parameters to measure similarity between individual trees in ensemble.I think the most suitable ones are nodeSize, nodeProbability and nodeError. But when I watch the results of them, the mean of their values for individual trees do not regularly increase or decrease. So I am not be able to draw a conclusion. Could you suggest anything else for this? My code snippet for one model is below: t = templateTree('MaxNumSplits',cell2mat(treeDepth)); % Weak-learner template tree object C1 = fitcensemble(X_train,Y_train,'Method','RUSBoost','Learners',t); [labels,scores] = predict(C1,X_test); meanSuccessRate=calculateMeanSuccessRate(scores,labels,Y_test); sonuclar(i,j)=meanSuccessRate; . . . nodeSize(d,z)=mean(C1.Trained{z}.NodeSize); nodeProbability(d,z)=mean(C1.Trained{z}.NodeProbability); nodeError(d,z)=mean(C1.Trained{z}.NodeError);
