Author(s)

Lan Wang and Hongsheng Xu

Corresponding Author

Hongsheng Xu

Abstract

Decision trees are generally generated from top to bottom, and each decision or event may lead to two or more events. Rough set is characterized by the use of imprecise, uncertain, partial real information to obtain easy to process, robust, low-cost decision-making scheme. Decision tree method is widely used in enterprise decision-making. Rough sets use upper and lower approximations to describe uncertainty, which makes the boundary clear and reduces the randomness of algorithm design. The paper presents construction of decision analysis system based on improved decision tree pruning algorithm and rough set classification Theory.

Keywords

Pruning algorithm, Decision tree, Rough set, C4.5 Algorithm, Classification reduction