نویسندگان | Mohammad Hossein Khosravi,Parsa Bagherzadeh |
---|---|
نشریه | Applied Intelligence |
شماره صفحات | 1172-1184 |
شماره سریال | 49 |
شماره مجلد | 3 |
ضریب تاثیر (IF) | 1.904 |
نوع مقاله | Full Paper |
تاریخ انتشار | 2018 |
رتبه نشریه | ISI |
نوع نشریه | چاپی |
کشور محل چاپ | ایران |
نمایه نشریه | JCR،Scopus |
چکیده مقاله
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.
tags: Intelligent water drops, Multi-objective optimization, Supervised feature selection, Class scatter matrices