Package: T4cluster 0.1.2

T4cluster: Tools for Cluster Analysis

Cluster analysis is one of the most fundamental problems in data science. We provide a variety of algorithms from clustering to the learning on the space of partitions. See Hennig, Meila, and Rocci (2016, ISBN:9781466551886) for general exposition to cluster analysis.

Authors:Kisung You [aut, cre]

T4cluster_0.1.2.tar.gz
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T4cluster.pdf |T4cluster.html✨
T4cluster/json (API)
NEWS

# Install 'T4cluster' in R:

install.packages('T4cluster', repos = c('https://kisungyou.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/kisungyou/t4cluster/issues

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3
openmp– GCC OpenMP (GOMP) support library

Datasets:

household - Load 'household' data

On CRAN:

44 exports 6 stars 1.59 score 106 dependencies 2 dependents 8 scripts 229 downloads

Last updated 3 years agofrom:cf15db5292. Checks:OK: 1 WARNING: 8. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Sep 03 2024
R-4.5-win-x86_64	WARNING	Sep 03 2024
R-4.5-linux-x86_64	WARNING	Sep 03 2024
R-4.4-win-x86_64	WARNING	Sep 03 2024
R-4.4-mac-x86_64	WARNING	Sep 03 2024
R-4.4-mac-aarch64	WARNING	Sep 03 2024
R-4.3-win-x86_64	WARNING	Sep 03 2024
R-4.3-mac-x86_64	WARNING	Sep 03 2024
R-4.3-mac-aarch64	WARNING	Sep 03 2024

Exports:ccphate compare.adjrand compare.rand consensus.auc consensus.pac dpmeans EKSS ephclust epmedoids funhclust funkmeans03A gbphate gen3S genDONUTS genLP genSMILEY gmm gmm03F gmm11R gmm16G gskmeans kmeans kmeans18B kmeanspp LRR LRSC LSR MSM pcm psm quality.CH quality.sil sc05Z sc09G sc10Z sc11Y sc12L scNJW scSM scUL spkmeans SSC SSQP testPHATE

Dependencies:ADMM ash base64enc bit bit64 bitops bslib cachem clarabel cli cluster codetools colorspace CVXR dbscan deSolve digest doParallel ECOSolveR evaluate fansi farver fastcluster fastmap fda fds FNN fontawesome foreach fs generics ggplot2 glue gmp gtable hdrcde highr htmltools htmlwidgets isoband iterators jquerylib jsonlite kernlab KernSmooth knitr ks labdsv labeling lattice lifecycle locfit lpSolve magrittr maotai MASS Matrix mclust mclustcomp memoise mgcv mime minpack.lm multicool munsell mvtnorm nlme osqp pcaPP pillar pkgconfig pracma R6 rainbow RANN rappdirs rbibutils RColorBrewer Rcpp RcppArmadillo RcppDE RcppDist RcppEigen RCurl Rdimtools Rdpack rgl rlang rmarkdown Rmpfr RSpectra rstiefel Rtsne sass scales scatterplot3d scs shapes tibble tinytex utf8 vctrs viridisLite withr xfun yaml

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Consensus Clustering with PHATE Geometry	ccphate
(+) Adjusted Rand Index	compare.adjrand
(+) Rand Index	compare.rand
Consensus Determination of K : Original Method	consensus.auc
Consensus Determination of K : PAC method	consensus.pac
DP-Means Clustering	dpmeans
Ensembles of K-Subspaces	EKSS
Hierarchical Agglomerative Clustering for Empirical Distributions	ephclust
K-Medoids Clustering for Empirical Distributions	epmedoids
Functional Hierarchical Clustering	funhclust
Functional K-Means Clustering by Abraham et al. (2003)	funkmeans03A
Generalized Bayesian Clustering with PHATE Geometry	gbphate
Generate from Three 5-dimensional Subspaces in 200-dimensional space.	gen3S
Generate Nested Donuts	genDONUTS
Generate Line and Plane Example with Fixed Number of Components	genLP
Generate SMILEY Data	genSMILEY
Finite Gaussian Mixture Model	gmm
Ensemble of Gaussian Mixtures with Random Projection	gmm03F
Regularized GMM by Ruan et al. (2011)	gmm11R
Weighted GMM by Gebru et al. (2016)	gmm16G
Geodesic Spherical K-Means	gskmeans
Load 'household' data	household
K-Means Clustering	kmeans
K-Means Clustering with Lightweight Coreset	kmeans18B
K-Means++ Clustering	kmeanspp
Low-Rank Representation	LRR
Low-Rank Subspace Clustering	LRSC
Least Squares Regression	LSR
Bayesian Mixture of Subspaces of Different Dimensions	MSM
Compute Pairwise Co-occurrence Matrix	pcm
S3 method to predict class label of new data with 'MSM' object	predict.MSM
Compute Posterior Similarity Matrix	psm
(+) CH index	quality.CH
(+) Silhouette Index	quality.sil
Spectral Clustering by Zelnik-Manor and Perona (2005)	sc05Z
Spectral Clustering by Gu and Wang (2009)	sc09G
Spectral Clustering by Zhang et al. (2010)	sc10Z
Spectral Clustering by Yang et al. (2011)	sc11Y
Spectral Clustering by Li and Guo (2012)	sc12L
Spectral Clustering by Ng, Jordan, and Weiss (2002)	scNJW
Spectral Clustering by Shi and Malik (2000)	scSM
Spectral Clustering with Unnormalized Laplacian	scUL
Spherical K-Means Clustering	spkmeans
Sparse Subspace Clustering	SSC
Subspace Segmentation via Quadratic Programming	SSQP
test using PHATE	testPHATE