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Feature selection plays an important role in the area of machine learning. Class Label is often used as the supervised information for supervised feature selection algorithm while constraints are rarely used. So, an effective feature selection algorithm with pairwise constraints called Constraints Score was proposed. But its performance still is limited by neglecting the correlation between features...
Many Semi-supervised learning applications require a feature selection method to deal with the unlabeled samples. Traditional researches deal it either with the "filter-type" feature selection mechanism, which may not work well for classification tasks or "wrapper" mechanism, which need high computational cost. Here we proposed a new semi-supervised feature selection method based...
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