Fuzzy decision trees and numerical attributes

Classical crisp decision trees (DT) are widely applied to classification tasks. Nevertheless, there are also a lot of fuzzy decision tree (FDT) solutions. Sometimes fuzzy borders for discretisation of continuous-valued attributes are used. The induction of FDT in these solutions need some parameters from the expert or user. An automatically generated membership function for discretisation of continuous-valued attributes is described in this paper. An example with the decision tree construction and the unseen data classification is given. The results of crisp and fuzzy decision trees are compared at the end.