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date: 31 March 2020

Abstract and Keywords

The term data mining refers to a variety of exploratory data analysis techniques developed in computer sciences and computational statistics. This chapter points out the commonalities and differences between data mining and classical statistical modeling. Common features of data mining techniques are then illustrated by means of one particular class of data mining techniques: the recursive partitioning methods classification and regression trees, bagging and random forests. In the end of the chapter an outlook on other popular data mining techniques as well as a short literature and software guide are given.

Keywords: Classification and regression trees, CART, Bagging, Random forests, Bootstrap sampling, Subsampling, Prediction, Variable importance

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