Miguel García-Remesal

A Selective Under-Sampling (SUS) Method for Imbalanced Regression (Abstract Reprint)

Many mainstream machine learning approaches, such as neural networks, are not well suited to work with imbalanced data. Yet, this problem is frequently present in many real-world data sets. Collection methods are imperfect, and often not able to capture enough data in a specific range of the target