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A hybrid model for class noise detection using k-means and classification filtering algorithms

Real data may have a considerable amount of noise produced by error in data collection, transmission and storage. The noisy training data set increases the training time and complexity of the induced machine learning model, which led to reduce the overall performance. Identifying noisy instances and...

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Main Authors:	Nematzadeh, Zahra, Ibrahim, Roliana, Selamat, Ali
格式:	Article
語言:	English
出版:	Springer, Cham 2020
在線閱讀:	http://eprints.utm.my/id/eprint/93683/1/AliSelamat2020_AHybridModelForClassNoiseDetection.pdf http://eprints.utm.my/id/eprint/93683/ http://dx.doi.org/10.1007/s42452-020-3129-x
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