Ensemble method, decision tree, random forest and boosting - PowerPoint Presentation

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Ensemble method, decision tree, random forest and boosting
Ensemble method, decision tree, random forest and boosting

Ensemble method, decision tree, random forest and boosting - Description


Zhiqi Peng Key concepts of supervised learning Objective function is training loss measure how well model fit on training data is regularization measures complexity of model   Key concepts of supervised learning ID: 721720 Download Presentation

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error tree training trees tree error trees training variance random ensemble define classification model bias set boosting split learning

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