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:Yuan Tang [aut, cre], Tao Gao [aut], Nan Xiao [aut]

dml_1.1.0.9001.tar.gz
dml_1.1.0.9001.zip(r-4.7)dml_1.1.0.9001.zip(r-4.6)dml_1.1.0.9001.zip(r-4.5)
dml_1.1.0.9001.tgz(r-4.6-any)dml_1.1.0.9001.tgz(r-4.5-any)
dml_1.1.0.9001.tar.gz(r-4.7-any)dml_1.1.0.9001.tar.gz(r-4.6-any)
dml_1.1.0.9001.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
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

On CRAN:

Conda:

dimensionality-reductiondistance-metric-learningmachine-learningmetric-learningstatistics

5.98 score 58 stars 1 packages 11 scripts 230 downloads 4 exports 8 dependencies

Last updated from:68558d8b81. Checks:7 ERROR, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64ERROR130
source / vignettesOK166
linux-release-x86_64ERROR132
macos-release-arm64ERROR150
macos-oldrel-arm64ERROR75
windows-develERROR95
windows-releaseERROR88
windows-oldrelERROR88
wasm-releaseOK98

Exports:dcaGdmDiagGdmFullrca

Dependencies:latticelfdaMatrixplyrrARPACKRcppRcppEigenRSpectra