Feature selection for support vector regression using probabilistic prediction
10.1145/1835804.1835849
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sg-nus-scholar.10635-734662015-02-18T02:45:28Z Feature selection for support vector regression using probabilistic prediction Yang, J.-B. Ong, C.-J. MECHANICAL ENGINEERING Feature ranking Feature selection Probabilistic predictions Random permutation Support vector regression 10.1145/1835804.1835849 Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 343-351 2014-06-19T05:35:27Z 2014-06-19T05:35:27Z 2010 Conference Paper Yang, J.-B.,Ong, C.-J. (2010). Feature selection for support vector regression using probabilistic prediction. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining : 343-351. ScholarBank@NUS Repository. <a href="https://doi.org/10.1145/1835804.1835849" target="_blank">https://doi.org/10.1145/1835804.1835849</a> 9781450300551 http://scholarbank.nus.edu.sg/handle/10635/73466 NOT_IN_WOS Scopus |
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Feature ranking Feature selection Probabilistic predictions Random permutation Support vector regression |
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Feature ranking Feature selection Probabilistic predictions Random permutation Support vector regression Yang, J.-B. Ong, C.-J. Feature selection for support vector regression using probabilistic prediction |
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10.1145/1835804.1835849 |
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MECHANICAL ENGINEERING |
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MECHANICAL ENGINEERING Yang, J.-B. Ong, C.-J. |
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Conference or Workshop Item |
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Yang, J.-B. Ong, C.-J. |
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Yang, J.-B. |
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Feature selection for support vector regression using probabilistic prediction |
title_short |
Feature selection for support vector regression using probabilistic prediction |
title_full |
Feature selection for support vector regression using probabilistic prediction |
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Feature selection for support vector regression using probabilistic prediction |
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Feature selection for support vector regression using probabilistic prediction |
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feature selection for support vector regression using probabilistic prediction |
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2014 |
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http://scholarbank.nus.edu.sg/handle/10635/73466 |
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1681087753399304192 |