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
Browse package contents
Package details |
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| Author | Tao Gao <joegaotao@gmail.com>, Nan Xiao <me@nanx.me>, Yuan Tang <terrytangyuan@gmail.com> |
| Maintainer | Yuan Tang <terrytangyuan@gmail.com> |
| License | MIT + file LICENSE |
| Version | 1.0.0 |
| URL | https://github.com/nanxstats/sdml |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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