Important Techniques to Handle Imbalanced Data in Machine Learning Python

How to Handle Imbalanced Data in ML Classification using Python

In this article, we will discuss what is Imbalanced Data, the Metrics we should use to evaluate the model with Imbalanced Data, and the Techniques used to Handle Imbalanced Data.

While doing binary classification, almost every data scientist might have encountered the problem of handling Imbalanced Data. Generally Imbalanced data occurs when the datasets are distributed unequally i.e. when the frequency of data points or the number of rows in …

data handling-imbalanced-data machine machine learning nearmiss-algorithm oversampling python smote undersampling