A conditional opposition-based particle swarm optimisation for feature selection
Because of the existence of irrelevant, redundant, and noisy attributes in large datasets, the accuracy of a classification model has degraded. Hence, feature selection is a necessary pre-processing stage to select the important features that may considerably increase the efficiency of underlying cl...
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| 主要な著者: | , , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Taylor & Francis Group
2022-12-01
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| シリーズ: | Connection Science |
| 主題: | |
| オンライン･アクセス: | http://dx.doi.org/10.1080/09540091.2021.2002266 |
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