On relationships between imbalance and overlapping of datasets

Waleed Almutairi, R. Janicki
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引用次数: 3

Abstract

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 classification algorithms, namely, Decision Tree, KNN (k-Nearest Neighbors) and SVM (Support Vector Machines) classifiers are analyzed and compared.
数据集不平衡与重叠的关系
本文讨论了数据集不平衡和重叠经常遇到的问题。讨论了有重叠和没有重叠的不平衡数据集的准确性、精密度和召回率等性能指标,并与有重叠的平衡数据集的相同性能指标进行了比较。分析比较了三种流行的分类算法,即决策树、KNN (k-Nearest Neighbors)和SVM (Support Vector Machines)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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