Tuning a multiple classifier system for side effect discovery using genetic algorithms
In previous work, a novel supervised framework implementing a binary classifier was presented that obtained excellent results for side effect discovery. Interestingly, unique side effects were identified when different binary classifiers were used within the framework, prompting the investigation of...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Published: |
IEEE
2014
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| Subjects: | |
| Online Access: | https://eprints.nottingham.ac.uk/3354/ |