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- W110792237 abstract "Feature selection methods obtain their optimal feature subsets by a strategy of weighting features according to their contribution to classification. Margin and rough sets are widely discussed in feature evaluation these years. However, no work has been contributed to compare their performance. In this paper, we introduce four feature weighting algorithms. WDL-MFD and FD-ranking, are designed based on fuzzy rough sets. They use fuzzy dependency as their feature evaluation criterion. While the other two, Simba and Relief, use margin to measure the significance of the features. In our work, we give a theoretical and empirical analysis and experimentally compare the two kinds of feature evaluation techniques, and demonstrate their detailed difference and connection. The experimental results show there is no significant difference among the performance obtained with different techniques." @default.
- W110792237 created "2016-06-24" @default.
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- W110792237 date "2012-01-01" @default.
- W110792237 modified "2023-09-26" @default.
- W110792237 title "Comparative Analysis on Margin and Fuzzy Rough Sets Based Feature Selection" @default.
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- W110792237 doi "https://doi.org/10.1007/978-3-642-32115-3_44" @default.
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