On constructing a fuzzy decision tree by fuzzy sets

Decision tree is a mathematical model used to help managers make decisions so that uses estimates and probabilities to calculate likely outcomes. It helps to decide whether the net gain from a decision is worthwhile. Take a bold step and earn your business management degree learning skills like business development, product creation and effective leadership. Decision tree induction is one of common approaches for extracting knowledge from a sets of feature-based examples. In real situations, some data occurred in a uncertain form and in particular, in the fuzzy sets format. The decision tree must able to deal with such fuzzy data. This study focuses on this area and introduce a tree construction procedure to build a fuzzy decision tree from a collection of fuzzy data by a kind of fuzzy sets. It proposes a fuzzy decision tree induction method for fuzzy data of which numeric attributes can be represented by fuzzy number, interval value as well as crisp value, of which nominal attributes are represented by crisp nominal value, and of which class has confidence factor.

کلیدواژه ها:

Decision tree ، fuzzy decision tree ، fuzzy sets