Handling highly imbalanced output class label: a case study on Fantasy Premier League (FPL) virtual player price changes prediction using machine learning / Muhammad Muhaimin Khamsan and Ruhaila Maskat
In practice, a balanced target class is rare. However, an imbalanced target class can be handled by resampling the original dataset, either by oversampling/upsampling or undersampling/downsampling. A popular upsampling technique is Synthetic Minority Over-sampling Technique (SMOTE). This technique i...
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| Päätekijät: | , |
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| Aineistotyyppi: | Kirja |
| Julkaistu: |
Penerbit UiTM,
2019-12.
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| Aiheet: | |
| Linkit: | Link Metadata |
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Internet
Link Metadata3rd Floor Main Library
| Hyllypaikka: |
A1234.567 |
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| Nide 1 | Saatavissa |