Package: treeClust 1.1-7.1
treeClust: Cluster Distances Through Trees
Create a measure of inter-point dissimilarity useful for clustering mixed data, and, optionally, perform the clustering.
Authors:
treeClust_1.1-7.1.tar.gz
treeClust_1.1-7.1.zip(r-4.7)treeClust_1.1-7.1.zip(r-4.6)treeClust_1.1-7.1.zip(r-4.5)
treeClust_1.1-7.1.tgz(r-4.6-any)treeClust_1.1-7.1.tgz(r-4.5-any)
treeClust_1.1-7.1.tar.gz(r-4.7-any)treeClust_1.1-7.1.tar.gz(r-4.6-any)
treeClust_1.1-7.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
treeClust/json (API)
| # Install 'treeClust' in R: |
| install.packages('treeClust', repos = c('https://buttrey.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:12261a45f4. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 94 | ||
| source / vignettes | OK | 131 | ||
| linux-release-x86_64 | OK | 85 | ||
| macos-release-arm64 | OK | 138 | ||
| macos-oldrel-arm64 | OK | 201 | ||
| windows-devel | OK | 59 | ||
| windows-release | OK | 63 | ||
| windows-oldrel | OK | 59 | ||
| wasm-release | OK | 100 |
Exports:cramerd3.distleaf.numbersmake.leaf.pathsrp.deviancerpart.predict.leavestcdisttcnewdatatreeClusttreeClust.controltreeClust.disttreeClust.rpart
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Compute Cramer's V for a two-way table | cramer |
| D3-style dissimilarity for a single tree | d3.dist |
| Convert "where" entry of tree frame into leaf numbers | leaf.numbers |
| Make matrix of leaf paths | make.leaf.paths |
| Plot treeClust object | plot.treeClust |
| Print treeClust object | print.treeClust |
| Compute deviance within nodes of classification trees | rp.deviance |
| Return the leaf into which observations are predicted to fall | rpart.predict.leaves |
| Summarize treeClust object | summary.treeClust |
| Compute treeClust dissimilarities | tcdist |
| Create all-numeric data to mimic the inter-point distances from treeClust | tcnewdata |
| Build a tree-based dissimilarity for clustering, and optionally perform the clustering | treeClust |
| Parameters describing the output from a treeClust fit | treeClust.control |
| Built treeClust distance | treeClust.dist |
| Build an rpart tree as part of treeClust | treeClust.rpart |
