Multi-label learning with label-specific feature reduction

    Knowl.-Based Syst., Volume 104, Issue C, 2016, Pages 52-61.

    Cited by: 38|Bibtex|Views21|Links
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    Abstract:

    We propose two multi-label learning approaches with LIFT reduction.The idea of fuzzy rough set attribute reduction is adopted in our approaches.Sample selection improves the efficiency in feature dimension reduction. In multi-label learning, since different labels may have some distinct characteristics of their own, multi-label learning a...More

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