road2stat/sdml: Supervised Distance Metric Learning with R

The sdml package aims to implement the state-of-the-art algorithms for supervised distance metric learning. It includes global and local methods such as (Kernel) Relevant Component Analysis, (Kernel) Discriminative Component Analysis, (Kernel) 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.

Getting started

Package details

AuthorTao Gao <[email protected]>, Nan Xiao <[email protected]>, Yuan Tang <[email protected]>
MaintainerYuan Tang <[email protected]>
LicenseMIT + file LICENSE
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
road2stat/sdml documentation built on May 25, 2017, 5:19 a.m.