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Improving the classification performance on imbalanced data sets via new hybrid parameterisation model

The aim of this work is to analyse the performance of the new proposed hybrid parameterisation model in handling problematic data. Three types of problematic data will be highlighted in this paper: i) big data set, ii) uncertain and inconsistent data set and iii) imbalanced data set. The proposed hy...

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書誌詳細
主要な著者:	Mohamad, M., Selamat, A., Subroto, I. M., Krejcar, O.
フォーマット:	論文
言語:	English
出版事項:	King Saud bin Abdulaziz University 2021
主題:	QA75 Electronic computers. Computer science
オンライン･アクセス:	http://eprints.utm.my/id/eprint/95554/1/AliSelamat2021_ImprovingtheClassificationPerformance.pdf http://eprints.utm.my/id/eprint/95554/ http://dx.doi.org/10.1016/j.jksuci.2019.04.009
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