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Multi-label classification is an active research field in machine learning. Because of the high dimensionality of multi-label data, attribute reduction (also known as feature selection) is often necessary to improve multi-label classification performance. Rough set theory has been widely used for attribute reduction with much success. However, little work has been done on applying rough set theory...
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