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: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer, Cham
2020
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| Online Access: | 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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