Package: mob 0.4.2

mob: Monotonic Optimal Binning

Generate the monotonic binning and perform the woe (weight of evidence) transformation for the logistic regression used in the consumer credit scorecard development. The woe transformation is a piecewise transformation that is linear to the log odds. For a numeric variable, all of its monotonic functional transformations will converge to the same woe transformation.

Authors:WenSui Liu

mob_0.4.2.tar.gz
mob_0.4.2.zip(r-4.7-any)mob_0.4.2.zip(r-4.6-any)mob_0.4.2.zip(r-4.5-any)
mob_0.4.2.tgz(r-4.6-any)mob_0.4.2.tgz(r-4.5-any)
mob_0.4.2.tar.gz(r-4.7-any)mob_0.4.2.tar.gz(r-4.6-any)
mob_0.4.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
mob/json (API)

# Install 'mob' in R:
install.packages('mob', repos = c('https://statcompute.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/statcompute/mob/issues

Datasets:
  • hmeq - Credit attributes of 5,960 home equity loans

On CRAN:

Conda:

2.47 score 59 scripts 321 downloads 5 mentions 12 exports 8 dependencies

Last updated from:1e5cb564ad. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK103
source / vignettesOK167
linux-releaseOK105
macos-releaseOK106
macos-oldrelOK120
windows-develOK79
windows-releaseOK76
windows-oldrelOK80
wasm-releaseOK76

Exports:arb_binbad_binbatch_binbatch_woecal_woegbm_biniso_binkmn_binpool_binqcutqtl_binrng_bin

Dependencies:data.tabledigestgbmlatticeMatrixRboristRcppsurvival