An improvement direction for filter selection techniques using information theory measures and quadratic optimization

Waad Bouaguel; Ghazi Bel Mufti

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arXiv · 1208.3689

An improvement direction for filter selection techniques using information theory measures and quadratic optimization

Waad Bouaguel·Ghazi Bel Mufti

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Abstract

Filter selection techniques are known for their simplicity and efficiency. However this kind of methods doesn't take into consideration the features inter-redundancy. Consequently the un-removed redundant features remain in the final classification model, giving lower generalization performance. In this paper we propose to use a mathematical optimization method that reduces inter-features redundancy and maximize relevance between each feature and the target variable.

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Waad Bouaguel, Ghazi Bel Mufti. 2012-08-17. An improvement direction for filter selection techniques using information theory measures and quadratic optimization. https://arxiv.org/abs/1208.3689

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