An immune algorithm for generalized rule induction

Author

Jianguo, Zheng ; Lei, Wang ; Licheng, Jiao

Author_Institution

Nat. Lab of Radar Signal Process., Xidian Univ., Xi´´an, China

fYear

2001

fDate

2001

Firstpage

1023

Lastpage

1026

Abstract

Data mining usually means the efficient discovery of knowledge from databases, and the immune algorithm is a biological theory-based and globally searching algorithm. A specific immune algorithm is designed for discovering a few interesting, high-level prediction rules from databases, rather than discovering classification knowledge as usual in the literature. Three important data mining issues addressed by the algorithm are the interest of the discovered knowledge, the computational efficiency of the algorithm, and the tradeoff between expressiveness and efficiency

Keywords

computational complexity; data mining; genetic algorithms; knowledge representation; search problems; algorithm computational efficiency; biological theory-based algorithm; classification knowledge discovery; data mining; database knowledge discovery; discovered knowledge interest; evolutionary algorithm; expressiveness; generalized rule induction; genetic immune algorithm; globally searching algorithm; high-level prediction rules; tradeoff; Computational efficiency; Data mining; Databases; Dictionaries; Immune system; Immunity testing; Logic; Machine learning algorithms; Remuneration; Signal processing algorithms;

fLanguage

English

Publisher

ieee

Conference_Titel

Radar, 2001 CIE International Conference on, Proceedings

Conference_Location

Beijing

Print_ISBN

0-7803-7000-7

Type

conf

DOI

10.1109/ICR.2001.984884

Filename

984884