Package: treeClust 1.1-7
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.tar.gz
treeClust_1.1-7.zip(r-4.5)treeClust_1.1-7.zip(r-4.4)treeClust_1.1-7.zip(r-4.3)
treeClust_1.1-7.tgz(r-4.4-any)treeClust_1.1-7.tgz(r-4.3-any)
treeClust_1.1-7.tar.gz(r-4.5-noble)treeClust_1.1-7.tar.gz(r-4.4-noble)
treeClust_1.1-7.tgz(r-4.4-emscripten)treeClust_1.1-7.tgz(r-4.3-emscripten)
treeClust.pdf |treeClust.html✨
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 6 years agofrom:de73503565. Checks:OK: 5 NOTE: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 13 2024 |
| R-4.5-win | NOTE | Sep 13 2024 |
| R-4.5-linux | NOTE | Sep 13 2024 |
| R-4.4-win | OK | Sep 13 2024 |
| R-4.4-mac | OK | Sep 13 2024 |
| R-4.3-win | OK | Sep 13 2024 |
| R-4.3-mac | OK | Sep 13 2024 |
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 |
