Tag: Imbalance

In the previous story we explained how the naive random oversampling and random oversampling examples (ROSE) algorithms work. More importantly, we also defined the class imbalance problem and derived solutions for it with intuition. I highly recommend checking that story to ensure clear un...

Imbalanced classification is a common problem in machine learning, particularly in the realm of binary classification. This occurs when the training dataset has an unequal distribution of classes, leading to a potential bias in the trained model. Examples of imbalanced classification problems includ...