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Classifier Performance Estimation Under the Constraint of a Finite Sample Size: Resampling Schemes Applied to Neural Network Classifiers
In a practical classifier design problem, the sample size is limited, and the available finite sample needs to be used both to design a classifier and to predict the classifier’s performance for the true population. Since a larger sample is more representative of the population, it is advantageous t...
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| Autori principali: | , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
2007
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2729493/ https://ncbi.nlm.nih.gov/pubmed/18234468 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.neunet.2007.12.012 |
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