Abstract
The Machine Learning (ML) applications are an inseparable part of many research activities if not all. ML extracts information that is beyond human capacity. Thus, it identifies hidden relations in the dataset or makes predictions for the future. Also, the improvements in ML are an open research question. Between many aspects, imbalanced datasets reduce the ML performances significantly. ML algorithm predicts for the favor of the majority class. There are many attempts to overcome this problem. The most common method is an improvement on the dataset such as reducing the majority class or increasing minority class. In this presentation, we will explain the problem in detail and our recent attempts with the applications.