Robust Joint Feature Weights Learning Framework.

IEEE Transactions on Knowledge and Data Engineering(2016)

引用 30|浏览36
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摘要
Feature selection, selecting the most informative subset of features, is an important research direction in dimension reduction. The combinatorial search in feature selection is essentially a binary optimization problem, known as NP hard, which can be alleviated by learning feature weights. Traditional feature weights algorithms rely on heuristic search path. These approaches neglect the interacti...
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关键词
Optimization,Feature extraction,Robustness,Linear programming,Yttrium,Convergence,Sparse matrices
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