wevid
Quantifying Performance of a Binary Classifier Through Weight of Evidence
The distributions of the weight of evidence (log Bayes factor) favouring case over noncase status in a test dataset (or test folds generated by cross-validation) can be used to quantify the performance of a diagnostic test (McKeigue (2019), doi:10.1177/0962280218776989). The package can be used with any test dataset on which you have observed case-control status and have computed prior and posterior probabilities of case status using a model learned on a training dataset. To quantify how the predictor will behave as a risk stratifier, the quantiles of the distributions of weight of evidence in cases and controls can be calculated and plotted.
- Version0.6.2
- R versionunknown
- LicenseGPL-3
- Needs compilation?No
- wevid citation info
- Last release09/12/2019
Team
Marco Colombo
Paul McKeigue
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- Imports5 packages
- Suggests1 package