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Are open set classification methods effective on large-scale datasets?
Supervised classification methods often assume the train and test data distributions are the same and that all classes in the test set are present in the training set. However, deployed classifiers often require the ability to recognize inputs from outside the training set as unknowns. This problem...
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| 發表在: | PLoS One |
|---|---|
| Main Authors: | , , , , |
| 格式: | Artigo |
| 語言: | Inglês |
| 出版: |
Public Library of Science
2020
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| 主題: | |
| 在線閱讀: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7473573/ https://ncbi.nlm.nih.gov/pubmed/32886692 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0238302 |
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