Package: SMLoutliers 0.1

SMLoutliers: Outlier Detection Using Statistical and Machine Learning Methods

Local Correlation Integral (LOCI) method for outlier identification is implemented here. The LOCI method developed here is invented in Breunig, et al. (2000), see <doi:10.1145/342009.335388>.

Authors:Siddharth Jain and Prabhanjan Tattar

SMLoutliers_0.1.tar.gz
SMLoutliers_0.1.zip(r-4.7-any)SMLoutliers_0.1.zip(r-4.6-any)SMLoutliers_0.1.zip(r-4.5-any)
SMLoutliers_0.1.tgz(r-4.6-any)SMLoutliers_0.1.tgz(r-4.5-any)
SMLoutliers_0.1.tar.gz(r-4.7-any)SMLoutliers_0.1.tar.gz(r-4.6-any)
SMLoutliers_0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
SMLoutliers/json (API)

# Install 'SMLoutliers' in R:
install.packages('SMLoutliers', repos = c('https://siddjain24.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • stiff - The Board Stiffness Dataset

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 3 scripts 220 downloads 1 exports 0 dependencies

Last updated from:23fe068814. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK83
source / vignettesOK113
linux-releaseOK79
macos-releaseOK128
macos-oldrelOK161
windows-develOK59
windows-releaseOK53
windows-oldrelOK48
wasm-releaseOK70

Exports:LOCI

Dependencies: