A new method for feature selection based on intelligent water drops

被引:9
|
作者
Khosravi, Mohammad Hossein [1 ]
Bagherzadeh, Parsa [2 ]
机构
[1] Univ Birjand, Fac Elect & Comp Engn, Birjand, Iran
[2] Concordia Univ, Dept Comp Sci & Software Engn, Montreal, PQ, Canada
关键词
Intelligent water drops; Multi-objective optimization; Supervised feature selection; Class scatter matrices; PARTICLE SWARM OPTIMIZATION; GENETIC ALGORITHM; CLASSIFICATION; SUBSET; SVM;
D O I
10.1007/s10489-018-1313-0
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
One of the trending research areas of data mining and machine learning is feature selection. Feature selection is used as a technique for improving classification accuracy of a classifier as well as a more convenient way for visualization of data. In this paper, a new method for feature subset selection, based on intelligent water drops algorithm is proposed. Intelligent water drops algorithm is a metaheuristic algorithm which is inspired from movement of water drops in nature. In the proposed method, a new objective function which is suitable for intelligent water drops algorithm is introduced. The objective function is designed such that the selected feature vector would obtain a good classification accuracy as well as providing a good generalization degree. According to the experiments, the use of proposed approach leads to more accurate results as well as significant reduction in number of features.
引用
收藏
页码:1172 / 1184
页数:13
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