Package: npcs 0.1.1

npcs: Neyman-Pearson Classification via Cost-Sensitive Learning

We connect the multi-class Neyman-Pearson classification (NP) problem to the cost-sensitive learning (CS) problem, and propose two algorithms (NPMC-CX and NPMC-ER) to solve the multi-class NP problem through cost-sensitive learning tools. Under certain conditions, the two algorithms are shown to satisfy multi-class NP properties. More details are available in the paper "Neyman-Pearson Multi-class Classification via Cost-sensitive Learning" (Ye Tian and Yang Feng, 2021).

Authors:Ye Tian [aut], Ching-Tsung Tsai [aut, cre], Yang Feng [aut]

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5 exports 0.09 score 82 dependencies 15 scripts 187 downloads

Last updated 1 years agofrom:788e78e789. Checks:OK: 1 WARNING: 6. Indexed: yes.

Exports:cv.npcserror_rategamma_smotegenerate_datanpcs

Dependencies:caretclasscliclockcodetoolscolorspacecpp11data.tabledbscandfoptimdiagramdigestdplyre1071fansifarverFNNforcatsforeachformatRfuturefuture.applygenericsggplot2globalsgluegowergtablehardhatigraphipredisobanditeratorsKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixmgcvModelMetricsmunsellnlmennetnumDerivparallellypillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6RColorBrewerRcpprecipesreshape2rlangrpartscalesshapesmotefamilySQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr