Exploring clusters of rare events using unsupervised random forests
Given highly imbalanced data, most learning algorithms face the challenge of accurately predicting rare events, while such cases are the ones that carry importance and useful knowledge. In a binary class label dataset, the rare events are the ones in the minority class. This study used a stroke data...
Main Authors: | Z A Omar, Chin, Su Na, Siti Rahayu Mohd. Hashim, N Hamzah |
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Format: | Conference or Workshop Item |
Language: | English English |
Published: |
2022
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Subjects: | |
Online Access: | https://eprints.ums.edu.my/id/eprint/34420/1/FULL%20TEXT.pdf https://eprints.ums.edu.my/id/eprint/34420/2/ABSTRACT.pdf |
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