Package: clusterWebApp 0.1.3
clusterWebApp: Universal Clustering Analysis Platform
An interactive platform for clustering analysis and teaching based on the 'shiny' web application framework. Supports multiple popular clustering algorithms including k-means, hierarchical clustering, DBSCAN (Density-Based Spatial Clustering of Applications with Noise), PAM (Partitioning Around Medoids), GMM (Gaussian Mixture Model), and spectral clustering. Users can upload datasets or use built-in ones, visualize clustering results using dimensionality reduction methods such as Principal Component Analysis (PCA) and t-distributed Stochastic Neighbor Embedding (t-SNE), evaluate clustering quality via silhouette plots, and explore method-specific visualizations and guides. For details on implemented methods, see: Reynolds (2009, ISBN:9781598296975) for GMM; Luxburg (2007) <doi:10.1007/s11222-007-9033-z> for spectral clustering.
Authors:
clusterWebApp_0.1.3.tar.gz
clusterWebApp_0.1.3.zip(r-4.7)clusterWebApp_0.1.3.zip(r-4.6)clusterWebApp_0.1.3.zip(r-4.5)
clusterWebApp_0.1.3.tgz(r-4.6-any)clusterWebApp_0.1.3.tgz(r-4.5-any)
clusterWebApp_0.1.3.tar.gz(r-4.7-any)clusterWebApp_0.1.3.tar.gz(r-4.6-any)
clusterWebApp_0.1.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
clusterWebApp/json (API)
| # Install 'clusterWebApp' in R: |
| install.packages('clusterWebApp', repos = c('https://yjzhou16.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:a0b30e37f3. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 172 | ||
| source / vignettes | OK | 216 | ||
| linux-release-x86_64 | OK | 153 | ||
| macos-release-arm64 | OK | 139 | ||
| macos-oldrel-arm64 | OK | 190 | ||
| windows-devel | OK | 153 | ||
| windows-release | OK | 107 | ||
| windows-oldrel | OK | 142 | ||
| wasm-release | OK | 135 |
Exports:compute_silhouetteplot_elbowplot_radarplot_silhouetteprepare_datarun_apprun_clustering
Dependencies:abindbackportsbase64encbootbroombslibcachemcarcarDatacliclustercolorspacecommonmarkcorrplotcowplotcpp11crosstalkdbscandendextendDerivdigestdoBydplyrDTellipseemmeansestimabilityevaluatefactoextraFactoMineRfarverfastmapflashClustfontawesomeforecastFormulafracdifffsgenericsggplot2ggpubrggrepelggsciggsignifgluegridExtragtablehighrhtmltoolshtmlwidgetshttpuvisobandjquerylibjsonlitekernlabknitrlabelinglaterlatticelazyevalleapslifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmclustmemoisemgcvmicrobenchmarkmimeminqamlbenchmodelrmultcompViewmvtnormnlmenloptrnnetnumDerivotelpbkrtestpillarpkgconfigpolynompromisespurrrquantregR6rappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangrmarkdownrstatixRtsneS7sassscalesscatterplot3dshinyshinycssloadersshinythemessourcetoolsSparseMstringistringrsurvivaltibbletidyrtidyselecttimeDatetinytexurcautf8vctrsviridisviridisLitewithrxfunxtableyamlzoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Compute Average Silhouette Width | compute_silhouette |
| Plot Elbow Method for KMeans | plot_elbow |
| Plot Radar Chart for PAM Cluster Centers | plot_radar |
| Plot Silhouette Diagram | plot_silhouette |
| Prepare Built-in Datasets for Clustering | prepare_data |
| Launch the Shiny Clustering Web App | run_app |
| Perform clustering analysis | run_clustering |
