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Classification performance metrics that are derived from the ROC curve of a classifier. The package includes the H-measure performance metric as described in <http://link.springer.com/article/10.1007/s10994-009-5119-5>, which computes the minimum total misclassification cost, integrating over any uncertainty about the relative misclassification costs, as per a user-defined prior. It also offers a one-stop-shop for other scalar metrics of performance, including sensitivity, specificity and many others, and also offers plotting tools for ROC curves and related statistics.

copied from cf-staging / r-hmeasure
Type Size Name Uploaded Downloads Labels
conda 377.9 kB | noarch/r-hmeasure-1.0_2-r43hc72bb7e_3.conda  4 months and 27 days ago 380 main
conda 378.0 kB | noarch/r-hmeasure-1.0_2-r44hc72bb7e_3.conda  4 months and 27 days ago 400 main
conda 377.8 kB | noarch/r-hmeasure-1.0_2-r42hc72bb7e_2.conda  1 year and 5 months ago 836 main
conda 377.8 kB | noarch/r-hmeasure-1.0_2-r43hc72bb7e_2.conda  1 year and 5 months ago 867 main
conda 387.9 kB | noarch/r-hmeasure-1.0_2-r42hc72bb7e_1.tar.bz2  2 years and 1 month ago 1286 main
conda 388.0 kB | noarch/r-hmeasure-1.0_2-r41hc72bb7e_1.tar.bz2  2 years and 1 month ago 1250 main
conda 386.7 kB | noarch/r-hmeasure-1.0_2-r41hc72bb7e_0.tar.bz2  3 years and 4 months ago 1853 main
conda 386.6 kB | noarch/r-hmeasure-1.0_2-r40hc72bb7e_0.tar.bz2  3 years and 4 months ago 1843 main

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