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- W2394298484 abstract "This paper has presented a new bootstrap based method for ROC analysis of Fisher classifier(Fisher linear discrimi- nant).By defining Fisher classifier's output as a statistic,the bootstrap technique is used to obtain the sampling distributions of the out- puts for the positive class and the negative class respectively.As a result,the ROC curve is a plot of all the(False Positive Rate,True Positive Rate)pairs by varying the decision threshold over the whole range of the bootstrap distributions.Experiments on five data sets publicly available demonstrate,the confidence intervals for the bootstrap based ROC curves are much narrower than those of the ROC curves based on holdout or cross-validation,indicating a more precise ROC analysis of Fisher classifier." @default.
- W2394298484 created "2016-06-24" @default.
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- W2394298484 date "2008-01-01" @default.
- W2394298484 modified "2023-09-26" @default.
- W2394298484 title "ROC Analysis Based on Bootstrap Sampling Distributions" @default.
- W2394298484 hasPublicationYear "2008" @default.
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