Box drawings for learning with imbalanced data
The vast majority of real world classification problems are imbalanced, meaning there are far fewer data from the class of interest (the positive class) than from other classes. We propose two machine learning algorithms to handle highly imbalanced classification problems. The classifiers are disjun...
Main Authors: | Goh, Siong Thye (Contributor), Rudin, Cynthia (Contributor) |
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Other Authors: | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Operations Research Center (Contributor), Sloan School of Management (Contributor) |
Format: | Article |
Language: | English |
Published: |
Association for Computing Machinery (ACM),
2015-10-05T16:19:53Z.
|
Subjects: | |
Online Access: | Get fulltext |
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