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VMFS: A VIKOR-based multi-target feature selection
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DOI：10.1016/j.eswa.2021.115224.png)
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Abstract
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This paper proposed a Multi-Criteria Decision-Making (MCDM) modeling to deal with multi-target regression problem. This model offered a feature ranking approach for multi-target regression by one of the famous MCDM algorithms called VIKOR. In fact, in this approach, the multi-target feature selection has become an MCDM model in which features are evaluated based on relations with targets. Our proposed method, VIKOR-based Multi-target Feature Selection (VMFS), first uses cosine similarity to construct the decision matrix for the MCDM process. Then VIKOR method is applied to the decision matrix to rank the features in the multi-target space. To illustrate the optimality and efficiency of the proposed method, we have compared our approach with some multi-output feature selection methods. The results show that our method in terms of average RRMSE is superior to other similar methods and performs in a short time, and it is more efficient than the other methods.
Keywords:
Multi-criteria decision making
VIKOR method
Cosine similarity
Multi-target feature selection
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