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Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using Fuzzy and Rough Set Methods
This book presents novel classification algorithms for four challenging prediction tasks, namely learning from imbalanced, semi-supervised, multi-instance and multi-label data. The methods are based on fuzzy rough set theory, a mathematical framework used to model uncertainty in data. The book makes...
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| Materyal Türü: | e-Kitap |
| Dil: | İngilizce |
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Cham :
Springer International Publishing : Imprint: Springer,
2019.
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| Edisyon: | 1st ed. 2019. |
| Seri Bilgileri: | Studies in Computational Intelligence,
807 |
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| Online Erişim: | Full-text access OPAC'ta görüntüle |
Internet
Full-text accessOPAC'ta görüntüle
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