Package: outlierensembles 0.1.3

Sevvandi Kandanaarachchi

outlierensembles: A Collection of Outlier Ensemble Algorithms

Ensemble functions for outlier/anomaly detection. There is a new ensemble method proposed using Item Response Theory. Existing outlier ensemble methods from Schubert et al (2012) <doi:10.1137/1.9781611972825.90>, Chiang et al (2017) <doi:10.1016/j.jal.2016.12.002> and Aggarwal and Sathe (2015) <doi:10.1145/2830544.2830549> are also included.

Authors:Sevvandi Kandanaarachchi [aut, cre]

outlierensembles_0.1.3.tar.gz
outlierensembles_0.1.3.zip(r-4.7)outlierensembles_0.1.3.zip(r-4.6)outlierensembles_0.1.3.zip(r-4.5)
outlierensembles_0.1.3.tgz(r-4.6-any)outlierensembles_0.1.3.tgz(r-4.5-any)
outlierensembles_0.1.3.tar.gz(r-4.7-any)outlierensembles_0.1.3.tar.gz(r-4.6-any)
outlierensembles_0.1.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
outlierensembles/json (API)

# Install 'outlierensembles' in R:

install.packages('outlierensembles', repos = c('https://sevvandi.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/sevvandi/outlierensembles/issues

Pkgdown/docs site:https://sevvandi.github.io

On CRAN:

4.18 score 3 stars 10 scripts 192 downloads 6 exports 121 dependencies

Last updated from:0696979853. Checks:9 OK. Indexed: yes.

Target	Result	Time	Files	Syslog
linux-devel-x86_64	OK	147
source / vignettes	OK	193
linux-release-x86_64	OK	152
macos-release-arm64	OK	81
macos-oldrel-arm64	OK	75
windows-devel	OK	82
windows-release	OK	77
windows-oldrel	OK	73
wasm-release	OK	126

Exports:average_ensemble greedy_ensemble icwa_ensemble irt_ensemble max_ensemble threshold_ensemble

Dependencies:airt apcluster audio backports base64enc beepr brio bslib cachem callr checkmate class cli clipr cluster codetools colorspace cpp11 crayon data.table dcurver Deriv desc diffobj digest dplyr e1071 EstCRM evaluate farver fastmap fontawesome foreign Formula fs future future.apply generics ggplot2 globals glue GPArotation gridExtra gtable highr Hmisc htmlTable htmltools htmlwidgets isoband jquerylib jsonlite knitr labeling lattice lifecycle listenv magrittr MASS Matrix memoise mgcv mime mirai mirt mnormt nanonext nlme nnet parallelly pbapply permute pillar pkgbuild pkgconfig pkgload pracma praise processx progressr proxy ps psych purrr qs2 R.methodsS3 R.oo R.utils R6 rappdirs RColorBrewer Rcpp RcppArmadillo RcppParallel rlang rmarkdown rpart rprojroot rstudioapi S7 sass scales sessioninfo SimDesign splines2 stringfish stringi stringr testthat tibble tidyr tidyselect tinytex utf8 vctrs vegan viridisLite waldo withr xfun yaml

outlierensembles

Rendered fromoutlierensembles.Rmdusingknitr::rmarkdown

Last update: 2025-03-26
Started: 2021-06-06

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Uses the mean as the ensemble score	average_ensemble
Computes an ensemble score using the greedy algorithm proposed by Schubert et al (2012)	greedy_ensemble
Computes an ensemble score using inverse cluster weighted averaging method by Chiang et al (2017)	icwa_ensemble
Computes an ensemble score using Item Response Theory	irt_ensemble
Computes an ensemble score using the maximum score of each observation	max_ensemble
Computes an ensemble score by aggregating values above the mean	threshold_ensemble

Usage by other packages (reverse dependencies)