dml: Distance Metric Learning in R
Version 1.1.0

The 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.

Browse man pages Browse package API and functions Browse package files

AuthorYuan Tang <terrytangyuan@gmail.com>, Gao Tao <joegaotao@gmail.com>, Xiao Nan <road2stat@gmail.com>
Date of publication2015-08-29 13:14:59
MaintainerYuan Tang <terrytangyuan@gmail.com>
LicenseMIT + file LICENSE
Version1.1.0
URL https://github.com/terrytangyuan/dml
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("dml")

Man pages

dca: Discriminative Component Analysis
GdmDiag: Global Distance Metric Learning
GdmFull: Global Distance Metric Learning
rca: Relevant Component Analysis

Functions

GdmDiag Man page Source code
GdmFull Man page Source code
dca Man page Source code
rca Man page Source code

Files

tests
tests/testthat.R
tests/testthat
tests/testthat/test_helper_functions.R
tests/testthat/test_algorithms.R
NAMESPACE
NEWS
R
R/gdmf.r
R/aaa.R
R/rca.R
R/dca.R
R/gdmd.r
README.md
MD5
DESCRIPTION
man
man/rca.Rd
man/GdmFull.Rd
man/GdmDiag.Rd
man/dca.Rd
LICENSE
dml documentation built on May 19, 2017, 6:20 p.m.