The study of Rashomon effects on machine learning : a case study on breast cancer
The Rashomon effect is a theory that suggests the presence of multiple uncorrelated observations and explanations that can be made for a single observation. This theory has been translated into a popular machine learning method: Random Forests which uses bootstrapping (bagging) algorithms to create...
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| Format: | Final Year Project |
| Language: | English |
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Nanyang Technological University
2021
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| Online Access: | https://hdl.handle.net/10356/150018 |
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| Institution: | Nanyang Technological University |
| Language: | English |