PATTERN-CLASSIFICATION WITH GENETIC ALGORITHMS

被引：68
|
作者：
BANDYOPADHYAY, S [1 ]
MURTHY, CA [1 ]
PAL, SK [1 ]
机构：
[1] INDIAN STAT INST,MACHINE INTELLIGENCE UNIT,CALCUTTA 700035,W BENGAL,INDIA
来源：
PATTERN RECOGNITION LETTERS | 1995年 / 16卷 / 08期
关键词：
ELITIST MODEL; GENETIC OPERATORS; LINE FITTING; PATTERN RECOGNITION;
D O I：
10.1016/0167-8655(95)00052-I
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A method is proposed for finding decision boundaries, approximated by piecewise linear segments, for the classification of patterns in R(2), using an elitist model of a genetic algorithm. It involves the generation and placement of a set of lines (represented by strings) in the feature space that yields minimum misclassification. The effectiveness of the algorithm is demonstrated, for different parameter values, on both artificial data and speech data having non-linear class boundaries. Its comparison with the k-NN classifier is also made.
引用
收藏
页码：801 / 808
页数：8
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