Prediction model framework for imbalanced datasets
Generally, prediction requires significant and good quality input data that will give accurate prediction. However, real-data are often noisy, inconsistent and imbalanced. If the classes are imbalance, the class accuracy is unlikable because the prediction tends to favor those in majority class sinc...
| Autor principal: | |
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| Formato: | Tesis |
| Lenguaje: | inglés |
| Publicado: |
Quezon City
College of Engineering, University of the Philippines Diliman
2014.
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