Kernel methods for heterogeneous feature selection
نویسندگان
چکیده
منابع مشابه
Kernel methods for heterogeneous feature selection
This paper introduces two feature selection methods to deal with heterogeneous data that include continuous and categorical variables. We propose to plug a dedicated kernel that handles both kinds of variables into a Recursive Feature Elimination procedure using either a non-linear SVM or Multiple Kernel Learning. These methods are shown to offer state-of-the-art performances on a variety of hi...
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This paper introduces two feature selection methods to deal with heterogeneous data that include continuous and categorical variables. We propose to plug a dedicated kernel that handles both kind of variables into a Recursive Feature Elimination procedure using either a non-linear SVM or Multiple Kernel Learning. These methods are shown to offer significantly better predictive results than stat...
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ژورنال
عنوان ژورنال: Neurocomputing
سال: 2015
ISSN: 0925-2312
DOI: 10.1016/j.neucom.2014.12.098