Class imbalance problem in deep learning

1. What is class imbalance problem in deep learning?
2. Why class imbalance is a problem?
3. What is class imbalance problem give an example?

What is class imbalance problem in deep learning?

A classification data set with skewed class proportions is called imbalanced. Classes that make up a large proportion of the data set are called majority classes. Those that make up a smaller proportion are minority classes.

Why class imbalance is a problem?

Many practical classification problems are imbalanced. The class imbalance problem typically occurs when there are many more instances of some classes than others. In such cases, standard classifiers tend to be overwhelmed by the large classes and ignore the small ones.

What is class imbalance problem give an example?

Introduction. When observation in one class is higher than the observation in other classes then there exists a class imbalance. Example: To detect fraudulent credit card transactions. As you can see in the below graph fraudulent transaction is around 400 when compared with non-fraudulent transaction around 90000.