Handling Class Imbalance Problem

What is the Class Imbalance Problem? Data are said to suffer the Class Imbalance Problem when the class distributions are highly imbalanced. This is a scenario where the number of observations belonging to one class is significantly lower than those belonging to the other classes. Machine Learning algorithms tend to produce unacceptable predictions when faced with imbalanced datasets. Here in this article, we will see some of the techniques on how to handle the Class Imbalance Problem using R. Let's take data where the dependant variable is admission into college based on the independent variables such as GRE score, GPA score, and the ranking of the school.