Transcription of Classification and regression trees
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Classification and regression trees
Overview Classification and regression trees Wei-Yin Loh Classification and regression trees are machine-learning methods for constructing prediction models from data. The models are obtained by recursively partitioning the data space and fitting a simple prediction model within each partition. As a result, the partitioning can be represented graphically as a decision tree. Clas- sification trees are designed for dependent variables that take a finite number of unordered values, with prediction error measured in terms of misclassifica- tion cost.
Classification and regression trees Wei-Yin Loh ... solutions are linear discriminant analysis1 and near- ... neighbor models in the nodes. GUIDE also can pro-duce ensemble models using bagging16 and random forest17 techniques. Table 1 summarizes the features of the algorithms.
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