Novel discretization method for value domain partition of continuous attributes

This paper presented a novel heuristic method for value domain partition of continuous attributes.This approach defined a novel discretization function which could find optimal interval lists by means of interdependence between classes.In addition,it reasonably controlled information loss generated by discretization,so that decreased classification error.Empirical experiments and statistical analysis show that the appraoch can generate a better discretization scheme which significantly improves classification ability on C5.0 decision tree.