Rough Set based Attribute Clustering for Sample Classification of Gene Expression Data
نویسندگان
چکیده
منابع مشابه
Locally linear embedding and neighborhood rough set-based gene selection for gene expression data classification.
Cancer subtype recognition and feature selection are important problems in the diagnosis and treatment of tumors. Here, we propose a novel gene selection approach applied to gene expression data classification. First, two classical feature reduction methods including locally linear embedding (LLE) and rough set (RS) are summarized. The advantages and disadvantages of these algorithms were analy...
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ژورنال
عنوان ژورنال: Procedia Engineering
سال: 2012
ISSN: 1877-7058
DOI: 10.1016/j.proeng.2012.06.219