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Feature selection approach based on hypothesis-margin and pairwise constraints | IEEE Conference Publication | IEEE Xplore

Feature selection approach based on hypothesis-margin and pairwise constraints


Abstract:

In this paper, we propose a semi-supervised margin-based feature selection algorithm called Relief-Sc. It is a modification of the well-known Relief algorithm from its op...Show More

Abstract:

In this paper, we propose a semi-supervised margin-based feature selection algorithm called Relief-Sc. It is a modification of the well-known Relief algorithm from its optimization perspective. It utilizes cannot-link constraints only to solve a simple convex problem in a closed form giving a unique solution. Experimental results on well-known datasets validate the effectiveness of our proposed algorithm. Only with little supervision information, Relief-Sc proved to be comparable to supervised feature selection algorithms and was superior to the unsupervised ones.
Date of Conference: 18-20 April 2018
Date Added to IEEE Xplore: 04 June 2018
ISBN Information:
Conference Location: Jounieh, Lebanon

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