Feature selection in mixed data: A method using a novel fuzzy rough set-based information entropy
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- 作者：Xiao Zhanga ; zhangxiaoo@126.com" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae ; Changlin Meib ; clmei@mail.xjtu.edu.cn" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae ; Degang Chenc ; wscz973@163.com" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae ; Jinhai Lid ; jhlixjtu@163.com" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae
- 关键词：Mixed data ; Feature selection ; Fuzzy rough set theory ; Information entropy
- 刊名：Pattern Recognition
- 出版年：2016
- 出版时间：August 2016
- 年：2016
- 卷：56
- 期：Complete
- 页码：1-15
- 全文大小：754 K
文摘
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A novel fuzzy rough set-based information entropy is constructed for mixed data.
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The proposed entropy can equivalently characterize the existing attribute reductions in the fuzzy rough set theory.
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A feature selection algorithm is formulated based on the proposed entropy.
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A filter-wrapper method is suggested to select a best feature subset.
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