The aim of this contribution is to illustrate the role of statistical models and, more generally, of statistics, in choosing a Data Mining model. After a preliminary introduction on the distinction between Data Mining and statistics, we will focus on the issue of how to choose a Data Mining methodology. This well illustrates how statistical thinking can bring real added value to a Data Mining analysis, as otherwise it becomes rather difficult to make a reasoned choice. In the third part of the paper we will present, by means of a case study in credit risk management, how Data Mining and statistics can profitably interact.
CITATION STYLE
Giudici, P. (2009). Data Mining Model Comparison. In Data Mining and Knowledge Discovery Handbook (pp. 641–654). Springer US. https://doi.org/10.1007/978-0-387-09823-4_32
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