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Feb, 2018
处理不平衡多标签数据集中的难缩小分类问题
Dealing with Difficult Minority Labels in Imbalanced Mutilabel Data Sets
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Francisco Charte, Antonio J. Rivera, María J. del Jesus, Francisco Herrera
TL;DR
本研究深入分析了困难标签在多标签分类中的影响,并提出了一种新的解决方法,通过SCUMBLE和REMEDIAL度量标签的并发性并解耦高度不均衡的标签。
Abstract
multilabel classification
is an emergent data mining task with a broad range of real world applications. Learning from imbalanced multilabel data is being deeply studied latterly, and several
resampling methods
h
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