STAT 154 Lecture 22: Bagging
7 Nov 2018
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,"ti e min splines trees when the outcome is based on a. { model based fitting on the nature of the problem models versus. The that concept proportion are from of training k - observation in the m - th th class region think. A small value indicates that a node contains from a single class predominating observations. Final ima index we have better f- e. , find and with following 3 concepts: gini. Gini class fi index cation node impurity at region m : error. Fmx cm ) i ekta imrefun = cross - entropy or deviance. Single oob the class overall among prediction. B predictions is to fit observation a given bagged tree. , building training set predictions training data using the each original model the tree and averaging data c bootstrap ) a separate with all from prediction predictions , variable important tree residual is.
