Classification trees are used with a categorical response variable. The goal of a classification tree is to derive a model that predicts to which category a particular subject or individual belongs, based one or more explanatory factors. For example, we could use a classification tree to predict the diagnosis (Benign or Malignant) of a particular patient based upon information obtained by doctors through scanned images. These classification trees are displayed as a decision tree that has a start node which then branches into other nodes.

Data mining is the process of extracting useful information or patterns from large raw sets of data. In recent years the amount of data being collected has increased tremendously, which has resulted in the development of new and more complex data mining algorithms to go through the vast data. However, the rate of growth of the new computer systems does not equal the growth of the datasets and the complexity of these data mining algorithms.