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

5.98 score 58 stars 1 packages 11 scripts 428 downloads 4 exports 8 dependencies

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

TargetResultTimeFilesSyslog
linux-develERROR141
source / vignettesOK255
linux-releaseERROR140
macos-releaseERROR148
macos-oldrelERROR85
windows-develERROR84
windows-releaseERROR114
windows-oldrelERROR91
wasm-releaseOK123

Exports:dcaGdmDiagGdmFullrca

Dependencies:latticelfdaMatrixplyrrARPACKRcppRcppEigenRSpectra