Classification and regression tree models, also known as recursive partitioning or CARTTM, are a class of nonparametric regression models becoming increasingly popular in epidemiology and biomedical data analysis, as well as in the computer science and datamining fields. These models became popular when this methodology was formalized by Leo Breiman and colleagues in their book Classification and Regression Trees. Subsequent availability of commercial software (e.g., Salford Systems, Inc.) and academic freeware (R ‘tree’ and ‘rpart’ functions) for fitting these models helped make this approach practical to data analysis. One of the most common uses of classification and regression tree models in epidemiology is to develop predictive rules for diagnosis; other uses include developing screening guidelines and creating prognostic models.

The goal of regression and classification is ...

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