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-any)dml_1.1.0.9001.zip(r-4.6-any)dml_1.1.0.9001.zip(r-4.5-any)
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
DESCRIPTION |NEWS
card.svg |card.png
dml/json (API)

# 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

6.05 score 58 stars 1 packages 13 scripts 301 downloads 4 exports 8 dependencies

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

TargetResultTimeFilesSyslog
linux-devel-x86_64ERROR125
source / vignettesOK202
linux-release-x86_64ERROR138
macos-release-arm64ERROR111
macos-oldrel-arm64ERROR117
windows-develERROR97
windows-releaseERROR102
windows-oldrelERROR114
wasm-releaseOK120

Exports:dcaGdmDiagGdmFullrca

Dependencies:latticelfdaMatrixplyrrARPACKRcppRcppEigenRSpectra