Package: dml 1.1.0.9001
dml: Distance Metric Learning in R
State-of-the-art algorithms for distance metric learning, including global and local methods such as Relevant Component Analysis, Discriminative Component Analysis, Local Fisher Discriminant Analysis, etc. These distance metric learning methods are widely applied in feature extraction, dimensionality reduction, clustering, classification, information retrieval, and computer vision problems.
Authors:
dml_1.1.0.9001.tar.gz
dml_1.1.0.9001.zip(r-4.5)dml_1.1.0.9001.zip(r-4.4)dml_1.1.0.9001.zip(r-4.3)
dml_1.1.0.9001.tgz(r-4.4-any)dml_1.1.0.9001.tgz(r-4.3-any)
dml_1.1.0.9001.tar.gz(r-4.5-noble)dml_1.1.0.9001.tar.gz(r-4.4-noble)
dml_1.1.0.9001.tgz(r-4.4-emscripten)dml_1.1.0.9001.tgz(r-4.3-emscripten)
dml.pdf |dml.html✨
dml/json (API)
NEWS
| # Install 'dml' in R: |
| install.packages('dml', repos = c('https://terrytangyuan.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/terrytangyuan/dml/issues
dimensionality-reductiondistance-metric-learningmachine-learningmetric-learningstatistics
Last updated 1 years agofrom:68558d8b81. Checks:OK: 1 ERROR: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 29 2024 |
| R-4.5-win | ERROR | Oct 29 2024 |
| R-4.5-linux | ERROR | Oct 29 2024 |
| R-4.4-win | ERROR | Oct 29 2024 |
| R-4.4-mac | ERROR | Oct 29 2024 |
| R-4.3-win | ERROR | Oct 29 2024 |
| R-4.3-mac | ERROR | Oct 29 2024 |
Dependencies:latticelfdaMatrixplyrrARPACKRcppRcppEigenRSpectra
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Distance Metric Learning in R | dml-package |
| Discriminative Component Analysis | dca |
| Global Distance Metric Learning | GdmDiag |
| Global Distance Metric Learning | GdmFull |
| Print an dca object | print.dca |
| Print an GdmDiag object | print.GdmDiag |
| Print a gmdf object | print.gmdf |
| Print an rca object | print.rca |
| Relevant Component Analysis | rca |
