Title :
Study on discretization in rough set based on genetic algorithm
Author :
Chen, Cai-yun ; Li, Zhi-guo ; Qiao, Sheng-yong ; Wen, Shuo-pin
Author_Institution :
Center for Combinatorics, Nankai Univ., Tianjin, China
Abstract :
Discretization of attributes with real values in rough set is an important problem in data mining. It is different from the traditional discretization which has particular characteristic. Nguyen S. H has given a detailed description about discretization in rough set. This paper gives a genetic algorithm aimed at discretization proposed by Nguyen S. H. And at the same time we make an experiment on several datasets from UCI machine learning repository by this method. During the experiment, we constantly optimized genetic algorithm by adopting some optimization strategies. The experiment has proved that using genetic algorithm to solve discretization of rough set is efficient whatever in time complexity or in accuracy.
Keywords :
data mining; genetic algorithms; learning (artificial intelligence); rough set theory; data mining; genetic algorithm; machine learning repository; rough set discretization; Algorithm design and analysis; Combinatorial mathematics; Cybernetics; Data mining; Electronic mail; Genetic algorithms; Heuristic algorithms; Machine learning; Machine learning algorithms; NP-hard problem;
Conference_Titel :
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN :
0-7803-8131-9
DOI :
10.1109/ICMLC.2003.1259717
