Package: cml 0.3.1
Anh Tuan Bui
cml: Conditional Manifold Learning
Finds a low-dimensional embedding of high-dimensional data, conditioning on available manifold information.
Authors:
cml_0.3.1.tar.gz
cml_0.3.1.tar.gz(r-4.7-any)cml_0.3.1.tar.gz(r-4.6-any)
cml_0.3.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
cml/json (API)
| # Install 'cml' in R: |
| install.packages('cml', repos = c('https://cran.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:25009cc1cb. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 120 | ||
| source / vignettes | OK | 184 | ||
| linux-release-x86_64 | OK | 118 | ||
| wasm-release | OK | 88 |
Exports:ccorcondDistcondDist2condIsomapcondMDScondMDSeigencondSmacofcondSmacof_merczmpinv
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Conditional Manifold Learning | cml-package cml |
| Canonical Correlations | ccor |
| Conditional Euclidean distance | condDist condDist2 |
| Conditional ISOMAP | condIsomap |
| Conditional Multidimensional Scaling | condMDS |
| Conditional Multidimensional Scaling With Closed-Form Solution | condMDSeigen |
| Conditional SMACOF | condSmacof |
| Conditional SMACOF with incomplete conditioning data (missing entire row) | condSmacof_mer |
| C(Z) | cz |
| Moore-Penrose Inverse | mpinv |