An enhanced hybrid feature selection technique using term frequency-inverse document frequency and support vector machine-recursive feature elimination for sentiment classification
Sentiment classification is increasingly used to automatically identify a positive or negative sentiment in a text review. In classification, feature selection had always been a critical and challenging problem. Most of the related feature selection for sentiment classification techniques unable to...
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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: |
IEEE
2021
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| 主題: | |
| オンライン･アクセス: | http://umpir.ump.edu.my/id/eprint/31646/2/An%20enhanced%20hybrid%20feature%20selection%20technique%20using%20term%20frequency-inverse%20document%20frequency%20and%20support%20vector%20machine-recursive%20feature%20elimination%20for%20sentiment%20classification.pdf http://umpir.ump.edu.my/id/eprint/31646/ https://doi.org/10.1109/ACCESS.2021.3069001 https://doi.org/10.1109/ACCESS.2021.3069001 |
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http://umpir.ump.edu.my/id/eprint/31646/2/An%20enhanced%20hybrid%20feature%20selection%20technique%20using%20term%20frequency-inverse%20document%20frequency%20and%20support%20vector%20machine-recursive%20feature%20elimination%20for%20sentiment%20classification.pdfhttp://umpir.ump.edu.my/id/eprint/31646/
https://doi.org/10.1109/ACCESS.2021.3069001
https://doi.org/10.1109/ACCESS.2021.3069001