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  5. Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using Fuzzy and Rough Set Methods

Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using Fuzzy and Rough Set Methods

af Sarah Vluymans

indgår i Studies in Computational Intelligence serien

Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using Fuzzy and Rough Set Methods af Sarah Vluymans
Bag om 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.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9783030046620
  • Indbinding:
  • Hardback
  • Sideantal:
  • 249
  • Udgivet:
  • 5. december 2018
  • Udgave:
  • 12019
  • Vægt:
  • 571 g.
  • 8-11 hverdage.
  • 17. januar 2025
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This book presents novel classification algorithms for four challenging prediction tasks, namely learning from imbalanced, semi-supervised, multi-instance and multi-label data.

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