gaoming96/mcca: Multi-Category Classification Accuracy

It contains six common multi-category classification accuracy evaluation measures: Hypervolume Under Manifold (HUM), described in Li and Fine (2008) <doi:10.1093/biostatistics/kxm050>. Correct Classification Percentage (CCP), Integrated Discrimination Improvement (IDI), Net Reclassification Improvement (NRI), R-Squared Value (RSQ), described in Li, Jiang and Fine (2013) <doi:10.1093/biostatistics/kxs047>. Polytomous Discrimination Index (PDI), described in Van Calster et al. (2012) <doi:10.1007/s10654-012-9733-3>. Li et al. (2018) <doi:10.1177/0962280217692830>. We described all these above measures and our mcca package in Li, Gao and D'Agostino (2019) <doi:10.1002/sim.8103>.

Getting started

Package details

AuthorMing Gao, Jialiang Li
MaintainerMing Gao <gaoming@umich.edu>
LicenseGPL
Version0.5.0
URL https://github.com/gaoming96/mcca
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("gaoming96/mcca")
gaoming96/mcca documentation built on May 30, 2019, 6:55 p.m.