Imbalanced Multi-Label Classification: Balanced Weights May Not Improve Your Model Performance Compare the random forest model and logistic regression model with and without balanced weights on imbalanced multi-class classification

Imbalanced Multi-Label Classification: Balanced Weights May Not Improve Your Model Performance

The balanced weight is a widely used method for imbalanced classification models. It penalizes the wrong predictions about the minority classes by giving more weight to the loss function. In this tutorial, we will talk about how to use balanced weight for the imbalanced multi-label classification. We will cover the following: If you are interested …

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