R package dml: Distance Metric Learning in R. 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.
Keywords for this software
References in zbMATH (referenced in 3 articles )
Showing results 1 to 3 of 3.
- de Vazelhes, William; Carey, Cj; Tang, Yuan; Vauquier, Nathalie; Bellet, Aurélien: metric-learn: metric learning algorithms in Python (2020)
- Suárez, Juan Luis; García, Salvador; Herrera, Francisco: pyDML: a Python library for distance metric learning (2020)
- Yuan Tang, Wenxuan Li: lfda: An R Package for Local Fisher Discriminant Analysis and Visualization (2016) arXiv