Given a sample of class 0 and class 1 and a classification method, the package generates the corresponding Neyman-Pearson classifier with a pre-specified type-I error control and Neyman-Pearson Receiver Operating Characteristics.
Version: | 2.0.4 |
Imports: | glmnet, e1071, randomForest, MASS, parallel, ada, stats, graphics |
Suggests: | knitr, rmarkdown |
Published: | 2017-01-13 |
Author: | Yang Feng, Jessica Li and Xin Tong |
Maintainer: | Yang Feng <yang.feng at columbia.edu> |
License: | GPL-2 |
URL: | http://arxiv.org/abs/1608.03109 |
NeedsCompilation: | no |
Materials: | ChangeLog |
CRAN checks: | nproc results |
Reference manual: | nproc.pdf |
Vignettes: |
nproc demo |
Package source: | nproc_2.0.4.tar.gz |
Windows binaries: | r-devel: nproc_2.0.4.zip, r-release: nproc_2.0.4.zip, r-oldrel: nproc_2.0.4.zip |
OS X Mavericks binaries: | r-release: nproc_2.0.4.tgz, r-oldrel: nproc_2.0.4.tgz |
Old sources: | nproc archive |
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