Chunk #31 — The Methods — How Do Classification and Regression Trees Work? — Splitting and Stopping

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An introduction to recursive partitioning: rationale, application, and characteristics of classification and regression trees, bagging, and random forests.

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This is evident, e.g., in the R2 statistic reflecting the portion of variance explained by the model, that increases with every parameter added to the model. For example, in the extreme case where as many parameters as observations are available, any parametric model will show a perfect fit on the learning data, yielding a value of R2 = 1, but will perform poorly in future samples.