Embedded feature selection for neural networks via learnable drop layer
M J JimÉnez-Navarro,
M MartÍnez-Ballesteros,
I S Brito
et al.
Abstract:Feature selection is a widely studied technique whose goal is to reduce the dimensionality of the problem by removing irrelevant features. It has multiple benefits, such as improved efficacy, efficiency and interpretability of almost any type of machine learning model. Feature selection techniques may be divided into three main categories, depending on the process used to remove the features known as Filter, Wrapper and Embedded. Embedded methods are usually the preferred feature selection method that efficien… Show more
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