Imbalanced datasets are a common challenge in data science, especially when dealing with classification problems. They occur when one class has significantly more samples than another, leading to ...

imbalanced-learn is a python package offering a number of re-sampling techniques commonly used in datasets showing strong between-class imbalance. It is compatible with scikit-learn and is part of ...

Experiment with a combination of these techniques to find the most effective approach for your specific dataset and machine learning algorithm. Initially I thought it is ok to use imbalanced ...

In this repo, we implement an easy-to-use PyTorch sampler ImbalancedDatasetSampler that is able to rebalance the class distributions when sampling from the imbalanced dataset estimate the sampling ...