Feature selection with MCP $$^2$$ 2 regularization

Volume: 31, Issue: 10, Pages: 6699 - 6709
Published: Apr 26, 2018
Abstract
Feature selection, as a fundamental component of building robust models, plays an important role in many machine learning and data mining tasks. Recently, with the development of sparsity research, both theoretical and empirical studies have suggested that the sparsity is one of the intrinsic properties of real world data and sparsity regularization has been applied into feature selection models successfully. In view of the remarkable...
Paper Details
Title
Feature selection with MCP $$^2$$ 2 regularization
Published Date
Apr 26, 2018
Volume
31
Issue
10
Pages
6699 - 6709
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