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Is there any good tutorial that explains how to weight the samples during successive iterations of constructing the decision trees for a sample training set? I want to specifically how to the weights are assigned after the first decision tree is constructed.

Decision tree is designed using Information Gain as an anchor and I am wondering how is this affected due to the misclassifications in the previous iterations being weighted.

Any good tutorial / example is highly appreciated.

London guy
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1 Answers1

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A Short Introduction to Boosting from Freund and Schapire supplies an example of the AdaBoost algorithm using Quinlan's C4.5 Decision Tree model.

Matthew Spencer
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