Package: adproclus 2.0.1.9000

adproclus: Additive Profile Clustering Algorithms

Obtain overlapping clustering models for object-by-variable data matrices using the Additive Profile Clustering (ADPROCLUS) method. Also contains the low dimensional ADPROCLUS method for simultaneous dimension reduction and overlapping clustering. For reference see Depril, Van Mechelen, Mirkin (2008) <doi:10.1016/j.csda.2008.04.014> and Depril, Van Mechelen, Wilderjans (2012) <doi:10.1007/s00357-012-9112-5>.

Authors:Henry Heppe [aut, cre, cph], Julian Rossbroich [aut], Jeffrey Durieux [aut], Tom Wilderjans [aut]

adproclus_2.0.1.9000.tar.gz
adproclus_2.0.1.9000.zip(r-4.7-any)adproclus_2.0.1.9000.zip(r-4.6-any)adproclus_2.0.1.9000.zip(r-4.5-any)
adproclus_2.0.1.9000.tgz(r-4.6-any)adproclus_2.0.1.9000.tgz(r-4.5-any)
adproclus_2.0.1.9000.tar.gz(r-4.7-any)adproclus_2.0.1.9000.tar.gz(r-4.6-any)
adproclus_2.0.1.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
adproclus/json (API)

# Install 'adproclus' in R:

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

Bug tracker:https://github.com/henry-heppe/adproclus/issues

Datasets:

CGdata - Randomly generated data with underlying overlapping clusters.

On CRAN:

3.48 score 3 stars 2 scripts 376 downloads 15 exports 121 dependencies

Last updated from:409deb4afb. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel	OK	174
source / vignettes	OK	202
linux-release	OK	160
macos-release	OK	169
macos-oldrel	OK	184
windows-devel	OK	123
windows-release	OK	91
windows-oldrel	OK	90
wasm-release	OK	170

Exports:adpc adproclus adproclus_low_dim cluster_means get_random get_rational get_semirandom mselect_adproclus mselect_adproclus_low_dim plot_cluster_network plot_profiles plot_scree_adpc plot_scree_adpc_preselected plot_vars_by_comp select_by_CHull

Dependencies:abind askpass backports base64enc bit bit64 bslib cachem checkmate cli clipr cluster colorspace commonmark corpcor corrplot cpp11 crayon crosstalk curl data.table digest dplyr DT evaluate farver fastmap fdrtool fontawesome foreign Formula fs generics ggplot2 ggrepel glasso glue GPArotation gridExtra gtable gtools highr Hmisc hms htmlTable htmltools htmlwidgets httpuv httr igraph isoband jpeg jquerylib jsonlite knitr labeling later lattice lavaan lazyeval lifecycle magrittr MASS Matrix matrixStats memoise mime mnormt multichull nlme NMFN nnet numDeriv openssl otel pbapply pbivnorm pillar pkgconfig plotly plyr png prettyunits progress promises psych purrr qgraph quadprog R6 rappdirs RColorBrewer Rcpp readr reshape2 rlang rmarkdown rpart rstudioapi S7 sass scales shiny shinythemes sourcetools stringi stringr sys tibble tidyr tidyselect tinytex tzdb utf8 vctrs viridisLite vroom withr xfun xtable yaml

Help page	Topics
Constructor for a (low dimensional) ADPROCLUS solution object	adpc
Additive profile clustering	adproclus
Low dimensional ADPROCLUS	adproclus_low_dim
Randomly generated data with underlying overlapping clusters.	CGdata
Cluster Means based on Original Variables	cluster_means
Generate initial random start	get_random
Generate start allocation based on a priori profiles	get_rational
Generate initial semi-random start	get_semirandom
Model selection helper for ADPROCLUS	mselect_adproclus
Model selection helper for low dimensional ADPROCLUS	mselect_adproclus_low_dim
Network plot of a (low dimensional) ADPROCLUS solution	plot_cluster_network
Plot profile matrix of ADPROCLUS solution	plot_profiles
Scree plot of (low dimensional) ADPROCLUS models	plot_scree_adpc
Scree plot of a pre-selection of low dimensional ADPROCLUS models	plot_scree_adpc_preselected
Plot variable to component matrix of ADPROCLUS solution	plot_vars_by_comp
Plotting a (low dimensional) ADPROCLUS solution	plot.adpc
Print basic information on ADPROCLUS solution	print.adpc
Print (low dimensional) ADPROCLUS summary	print.summary.adpc
Automatic Model Selection for ADPROCLUS with CHull Method	select_by_CHull
Summary of ADPROCLUS solution	summary.adpc

Package: adproclus 2.0.1.9000

adproclus: Additive Profile Clustering Algorithms

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