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
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

6.02 score 58 stars 1 packages 12 scripts 238 downloads 4 exports 8 dependencies

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

TargetResultTimeFilesSyslog
linux-devel-x86_64ERROR156
source / vignettesOK175
linux-release-x86_64ERROR138
macos-release-arm64ERROR116
macos-oldrel-arm64ERROR80
windows-develERROR96
windows-releaseERROR91
windows-oldrelERROR84
wasm-releaseOK98

Exports:dcaGdmDiagGdmFullrca

Dependencies:latticelfdaMatrixplyrrARPACKRcppRcppEigenRSpectra