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-4.5)hclusteasy_0.1.0.zip(r-4.4)hclusteasy_0.1.0.zip(r-4.3)
hclusteasy_0.1.0.tgz(r-4.4-any)hclusteasy_0.1.0.tgz(r-4.3-any)
hclusteasy_0.1.0.tar.gz(r-4.5-noble)hclusteasy_0.1.0.tar.gz(r-4.4-noble)
hclusteasy_0.1.0.tgz(r-4.4-emscripten)hclusteasy_0.1.0.tgz(r-4.3-emscripten)
hclusteasy.pdf |hclusteasy.html✨
hclusteasy/json (API)
NEWS
| # 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 5 months agofrom:b156f8e050. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 22 2024 |
| R-4.5-win | OK | Nov 22 2024 |
| R-4.5-linux | OK | Nov 22 2024 |
| R-4.4-win | OK | Nov 22 2024 |
| R-4.4-mac | OK | Nov 22 2024 |
| R-4.3-win | OK | Nov 22 2024 |
| R-4.3-mac | OK | Nov 22 2024 |
Exports:hcanormalizationpcaread.data
Dependencies:abindade4backportsbase64encbootbroombslibcachemcarcarDatacellrangerclasscliclusterclusterSimcolorspacecorrplotcowplotcpp11crayoncrosstalkdendextendDerivdigestdoBydplyrDTe1071ellipseemmeansestimabilityevaluatefactoextraFactoMineRfansifarverfastmapflashClustfontawesomeFormulafsgenericsggplot2ggpubrggrepelggsciggsignifgluegridExtragtablehighrhmshtmltoolshtmlwidgetshttpuvisobandjquerylibjsonliteknitrlabelinglaterlatticelazyevalleapslifecyclelme4magrittrMASSMatrixMatrixModelsmemoisemgcvmicrobenchmarkmimeminqamodelrmultcompViewmunsellmvtnormnlmenloptrnnetnumDerivpbkrtestpillarpixmappkgconfigplyrpolynomprettyunitsprogresspromisesproxypurrrquantregR6rappdirsRColorBrewerRcppRcppArmadilloRcppEigenreadxlrematchreshape2rlangrmarkdownrstatixsassscalesscatterplot3dspSparseMstringistringrsurvivaltibbletidyrtidyselecttinytexutf8vctrsviridisviridisLitewithrxfunyaml
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 |
