标题:Application of Clustering Analysis in Brain Gene Data Based on Deep Learning
作者:Suo, Yina; Liu, Tingwei; Jia, Xueyong; Yu, Fuxing
作者机构:[Suo, Yina; Yu, Fuxing] North China Univ Sci & Technol, Informat Engn Inst, Tangshan 063000, Peoples R China.; [Liu, Tingwei] Shandong Univ, Sch Mat 更多
通讯作者:Yu, Fuxing;Yu, FX
通讯作者地址:[Yu, FX]North China Univ Sci & Technol, Informat Engn Inst, Tangshan 063000, Peoples R China.
来源:IEEE ACCESS
出版年:2019
卷:7
页码:2947-2956
DOI:10.1109/ACCESS.2018.2886425
关键词:Deep belief network; fuzzy c-means algorithm; unsupervised learning;; brain gene data clustering
摘要:In the current research, cluster analysis has become a very good way to obtain biological information by analyzing the brain gene expression data. In recent years, many experts have used improved traditional clustering algorithm and a new clustering algorithm to mine brain gene expression data. First, the random Forest method is used to preprocess high-dimensional and high-complexity brain gene expression data. Then, a clustering model based on deep learning is proposed, and a clustering algorithm is implemented by using deep belief network (DBN) and fuzzy c-means algorithm (FCM). This model makes full use of the generality of unsupervised learning of deep learning and clustering technology, combines the advantages of deep learning with clustering, and makes clustering effect better and more convenient for clustering high-dimensional data.
收录类别:EI;SCOPUS;SCIE
WOS核心被引频次:1
Scopus被引频次:2
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85058633813&doi=10.1109%2fACCESS.2018.2886425&partnerID=40&md5=98fa25b339d504a3936e3bc82e2db805
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