The Partition platform recursively partitions data according to a relationship between the predictors and response values, creating a decision tree. Variations of partitioning go by many names and brand names: decision trees, CARTTM, CHAIDTM, C4.5, C5, and others. The technique is often considered as a data mining technique for the following reasons:
Predictors can be either continuous or categorical (nominal or ordinal). If a predictor is continuous, then the splits are created by a cutting value. The sample is divided into values below and above this cutting value. If a predictor is categorical, then the sample is divided into two groups of levels.