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Hellinger Distance Weighted Ensemble
The Hellinger Distance Weighted Ensemble (hdwe) method for batch learning and the binary classification data stream with occurring concept drifts and the imbalance among classes. -
Balanced-MixUp for Highly Imbalanced Medical Image Classification
Highly imbalanced datasets are ubiquitous in medical image classification problems. In such problems, it is often the case that rare classes associated to less prevalent... -
Empirical evaluation of imbalance data strategies
This research tested the following well known strategies to deal with binary imbalanced data on 82 different real life data sets -
Autoencoder& GANs for Imbalanced Multi-Omics
The proposed model is applied to two publicly available datasets, the first is the Cancer Genome Atlas (TCGA) Breast Invasive Carcinoma (BRCA) dataset, which contains DNA... -
Boosted SVM for Extracting Rules from Imbalanced Data
Boosted SVM for extracting rules from imbalanced data in application to prediction of the post-operative life expectancy in the lung cancer patients. -
ImVerde: Vertex-diminished random walk for learning network representation fr...
ImVerde: Vertex-diminished random walk for learning network representation from imbalanced data -
SML2010 Data Set
The dataset used in this paper is a real-world dataset for imbalanced regression problems.
