Multi-Cluster Feature Selection Based on Isometric Mapping

被引：0
|
作者：
Yadi Wang [1 ,2 ]
Zefeng Zhang [1 ,2 ]
Yinghao Lin [1 ,2 ]
机构：
[1] the Henan Key Laboratory of Big Data Analysis and Processing, Henan University
[2] the Institute of Data and Knowledge Engineering, School of Computer and Information Engineering, Henan University
来源：
IEEE/CAA Journal of Automatica Sinica | 2022年 / 9卷 / 03期
基金：
中国国家自然科学基金;
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论]; TP311.13 [];
学科分类号：
081104 ; 0812 ; 0835 ; 1201 ; 1405 ;
摘要：
Dear editor,This letter presents an unsupervised feature selection method based on machine learning. Feature selection is an important component of artificial intelligence, machine learning, which can effectively solve the curse of dimensionality problem. Since most of the labeled data is expensive to obtain,
引用
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页码：570 / 572
页数：3
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