process imbalanced data
5 Important Techniques To Process Imbalanced Data In Machine Learning
Imbalance data distribution is an important part of machine learning workflow. An imbalanced dataset means instances of one of the two classes is higher than the other, in another way, the number of observations is not the same for all the classes in a classification dataset. This problem is faced not only in the binary class data but also in the multi-class data. In this article, we list some important techniques that will help you to deal with your imbalanced data. This technique is used to modify the unequal data classes to create balanced datasets.