Salvador García

SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Anniversary

2018 · Journal of Artificial Intelligence Research

The Synthetic Minority Oversampling Technique (SMOTE) preprocessing algorithm is considered "de facto" standard in the framework of learning from imbalanced data. This is due to its simplicity in the design of the procedure, as well …

DPASF: a flink library for streaming data preprocessing

2019 · Big Data Analytics

Data preprocessing techniques are devoted to correcting or alleviating errors in data. Discretization and feature selection are two of the most extended data preprocessing techniques. Although we can find many proposals for static Big Data …