Package: cml 0.2.2

Anh Tuan Bui

cml: Conditional Manifold Learning

Finds a low-dimensional embedding of high-dimensional data, conditioning on available manifold information. The current version supports conditional MDS (based on either conditional SMACOF in Bui (2021) <arxiv:2111.13646> or closed-form solution in Bui (2022) <doi:10.1016/j.patrec.2022.11.007>) and conditional ISOMAP in Bui (2021) <arxiv:2111.13646>.

Authors:Anh Tuan Bui [aut, cre]

cml_0.2.2.tar.gz
cml_0.2.2.tar.gz(r-4.5-noble)cml_0.2.2.tar.gz(r-4.4-noble)
cml_0.2.2.tgz(r-4.4-emscripten)cml_0.2.2.tgz(r-4.3-emscripten)
cml.pdf |cml.html✨
cml/json (API)

# Install 'cml' in R:
install.packages('cml', repos = 'https://cloud.r-project.org')

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.30 score 310 downloads 2 mentions 9 exports 8 dependencies

Last updated 2 years agofrom:82a90e80a9. Checks:3 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 09 2025
R-4.5-linuxOKMar 09 2025
R-4.4-linuxOKMar 09 2025

Exports:ccorcondDistcondDist2condIsomapcondMDScondMDSeigencondSmacofczmpinv

Dependencies:clusterlatticeMASSMatrixmgcvnlmepermutevegan

Citation

To cite cml in publications, please use:

Anh Tuan Bui (2021). Dimension Reduction with Prior Information for Knowledge Discovery. arXiv:2111.13646. https://arxiv.org/abs/2111.13646.

Anh Tuan Bui (2022). A Closed-Form Solution for Conditional Multidimensional Scaling. Pattern Recognition Letters 164, 148-152. https://doi.org/10.1016/j.patrec.2022.11.007.

Corresponding BibTeX entries: 

  @Manual{,
    title = {Dimension Reduction with Prior Information for Knowledge
      Discovery},
    author = {Anh Tuan Bui},
    journal = {arXiv:2111.13646},
    year = {2021},
    volume = {164},
    pages = {148-152},
    url = {https://arxiv.org/abs/2111.13646},
  }

  @Manual{,
    title = {A Closed-Form Solution for Conditional Multidimensional
      Scaling},
    author = {Anh Tuan Bui},
    journal = {Pattern Recognition Letters},
    year = {2022},
    volume = {164},
    pages = {148-152},
    url = {https://doi.org/10.1016/j.patrec.2022.11.007},
  }