Sparse Penalized Forward Selection for Support Vector Classification
نویسندگان
چکیده
منابع مشابه
Sparse Penalized Forward Selection for Support Vector Classification
We propose a new binary classification and variable selection technique especially designed for high dimensional predictors. Among many predictors, typically, only a small fraction of them have significant impact on prediction. In such a situation, more interpretable models with better prediction accuracy can be obtained by variable selection along with classification. By adding an `1-type pena...
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Article history: Received 17 November 2009 Received in revised form 14 July 2010 Accepted 31 August 2010
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ژورنال
عنوان ژورنال: Journal of Computational and Graphical Statistics
سال: 2016
ISSN: 1061-8600,1537-2715
DOI: 10.1080/10618600.2015.1023395