Undersampling Technique – Tomek Links

Tomek Link Undersampling is a technique used to address class imbalance in machine learning datasets. It involves identifying Tomek links, which are pairs of instances from different classes that are nearest neighbors of each other, and removing instances from the majority class that form these links. The main idea behind Tomek Link Undersampling is to…

Oversampling Technique – SMOTE

SMOTE (Synthetic Minority Over-sampling Technique) is an upsampling technique used in machine learning to address the class imbalance problem, which occurs when the number of instances of one class (minority class) is significantly lower than the number of instances of the other class (majority class) in a dataset. This class imbalance can lead to biased…