MUTE: Majority under-sampling technique
An application which operates on an imbalanced dataset loses its classification performance on a minority class, which is rare and important. There are a number of over-sampling techniques, which insert minority instances into a dataset, to adjust the class distribution. Unfortunately, these instanc...
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Main Authors: | , , |
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Format: | Conference or Workshop Item |
Published: |
2015
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Online Access: | http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84860630816&origin=inward http://cmuir.cmu.ac.th/handle/6653943832/38626 |
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Institution: | Chiang Mai University |