Package: hclusteasy 0.1.0
Henrique Andrade
hclusteasy: Determining Hierarchical Clustering Easily
Facilitates hierarchical clustering analysis with functions to read data in 'txt', 'xlsx', and 'xls' formats, apply normalization techniques to the dataset, perform hierarchical clustering and construct scatter plot from principal component analysis to evaluate the groups obtained.
Authors:
hclusteasy_0.1.0.tar.gz
hclusteasy_0.1.0.zip(r-4.7-any)hclusteasy_0.1.0.zip(r-4.6-any)hclusteasy_0.1.0.zip(r-4.5-any)
hclusteasy_0.1.0.tgz(r-4.6-any)hclusteasy_0.1.0.tgz(r-4.5-any)
hclusteasy_0.1.0.tar.gz(r-4.7-any)hclusteasy_0.1.0.tar.gz(r-4.6-any)
hclusteasy_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
hclusteasy/json (API)
| # Install 'hclusteasy' in R: |
| install.packages('hclusteasy', repos = c('https://tsukubai.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/tsukubai/hclusteasy/issues
Last updated from:b156f8e050. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 165 | ||
| source / vignettes | OK | 227 | ||
| linux-release | OK | 155 | ||
| macos-release | OK | 160 | ||
| macos-oldrel | OK | 208 | ||
| windows-devel | OK | 96 | ||
| windows-release | OK | 108 | ||
| windows-oldrel | OK | 96 | ||
| wasm-release | OK | 125 |
Exports:hcanormalizationpcaread.data
Dependencies:abindade4backportsbase64encbootbroombslibcachemcarcarDatacellrangerclasscliclusterclusterSimcolorspacecorrplotcowplotcpp11crayoncrosstalkdendextendDerivdigestdoBydplyrDTe1071ellipseemmeansestimabilityevaluatefactoextraFactoMineRfarverfastmapflashClustfontawesomeforecastFormulafracdifffsgenericsggplot2ggpubrggrepelggsciggsignifgluegridExtragtablehighrhmshtmltoolshtmlwidgetsirlbaisobandjquerylibjsonliteknitrlabelinglaterlatticelazyevalleapslifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmemoisemgcvmimeminqamodelrmultcompViewmvtnormnlmenloptrnnetnumDerivotelpbkrtestpillarpixmappkgconfigpolynomprettyunitsprogresspromisesproxypurrrquantregR6rappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreadxlreformulasrematchrlangrmarkdownrstatixS7sassscalesscatterplot3dshowtextshowtextdbspSparseMstringistringrsurvivalsysfontstibbletidyrtidyselecttimeDatetinytexurcautf8vctrsviridisviridisLitewithrxfunyamlzoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Generate and Select Groups with Hierarchical Clustering | hca |
| Iris Dataset | iris_uci |
| Apply Normalization Techniques to the Dataset | normalization |
| Plot Principal Component Analysis Results | pca |
| Read Files in txt, xls, or xlsx Formats | read.data |
| Wine Dataset | wine_uci |