Multi-Cluster Feature Selection Based on Isometric Mapping

查看全文 作　　者：Yadi [1,2]Wang;Zefeng [1,2]Zhang;Yinghao [1,2]Lin

机构地区：[1]Henan Key Laboratory of Big Data Analysis and Processing,Henan University,Kaifeng 475004;[2]Institute of Data and Knowledge Engineering,School of Computer and Information Engineering,Henan University,Kaifeng 475004,China

出　　处：《IEEE/CAA Journal of Automatica Sinica》索引2022年第9卷第3期,共3页

基　　金：supported by grants from the National Natural Science Foundation of China(62106066);Key Research Projects of Henan Higher Education Institutions(22A520019);Scientific and Technological Project of Henan Province(202102110121);Science and Technology Development Project of Kaifeng City(2002001)。 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. 关键词：PROBLEM LETTER dimensionality

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Multi-Cluster Feature Selection Based on Isometric Mapping

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