A new classification model for a class imbalanced data set using genetic programming and support vector machines: case study for wilt disease classification
Class imbalanced data set is a state where each class of the given data set is not evenly distributed. When such case happens, most standard classifiers fail to recognize examples that belong to a minority class. Hence, several methods have been proposed to solve this problem such as resampling, mod...
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| 主要な著者: | , , , |
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| フォーマット: | 論文 |
| 言語: | English |
| 出版事項: |
Taylor & Francis
2015
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| オンライン･アクセス: | http://psasir.upm.edu.my/id/eprint/43520/1/A%20new%20classification%20model%20for%20a%20class%20imbalanced%20data%20set%20using%20genetic%20programming.pdf http://psasir.upm.edu.my/id/eprint/43520/ |
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