The paper deals with problems that imbalanced and overlapping datasets often encounter. Performance indicators as accuracy, precision and recall of imbalanced data sets, both with and without overlapping, are discussed and compared with the same performance indicators of balanced datasets with overlapping. Three popular classiffcation algorithms, namely, Decision Tree, KNN (k-Nearest Neighbors) and SVM (Support Vector Machines) classiffers are analyzed and compared.
CITATION STYLE
Almutairi, W. A., & Janicki, R. (2020). On relationships between imbalance and overlapping of datasets. In EPiC Series in Computing (Vol. 69, pp. 141–150). EasyChair. https://doi.org/10.29007/h71z
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