sdml-package: sdml: Supervised Distance Metric Learning with R

In road2stat/sdml: Supervised Distance Metric Learning with R

Description

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.

See Also

Useful links:

• https://github.com/nanxstats/sdml

• Report bugs at https://github.com/nanxstats/sdml/issues

road2stat/sdml documentation built on May 27, 2019, 10:31 a.m.