Radial-Based Oversampling for Multiclass Imbalanced Data Classification
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Neural Networks and Learning Systems"
DOI: 10.1109/tnnls.2019.2913673
Abstract: Learning from imbalanced data is among the most popular topics in the contemporary machine learning. However, the vast majority of attention in this field is given to binary problems, while their much more difficult multiclass… read more here.
Keywords: oversampling multiclass; based oversampling; imbalanced data; multiclass ... See more keywords
A Boundary-Information-Based Oversampling Approach to Improve Learning Performance for Imbalanced Datasets
Sign Up to like & getrecommendations! Published in 2022 at "Entropy"
DOI: 10.3390/e24030322
Abstract: Oversampling is the most popular data preprocessing technique. It makes traditional classifiers available for learning from imbalanced data. Through an overall review of oversampling techniques (oversamplers), we find that some of them can be regarded… read more here.
Keywords: information; boundary information; information based; samples near ... See more keywords