Chunk #52 — The Methods — How Do Classification and Regression Trees Work? — What is Wrong with Trees?

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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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The main flaw of simple tree models is their instability to small changes in the learning data: In recursive partitioning, the exact position of each cutpoint in the partition, as well as the decision which variable to split in, determines how the observations are split up in new nodes, in which splitting continues recursively. However, the exact position of the cutpoint, as well as the selection of the splitting variable, strongly depend on the particular distribution of observations in the learning sample.