Prototype-based Machine Learning on Distance Data

This scikit-learn compatible, Python3 library provides several algorithms to learn prototype models on distance data. At this time, this library features the following algorithms:

• Relational Neural Gas (Hammer and Hasenfuss, 2007) for clustering,
• Relational Generalized Learning Vector Quantization (Hammer, Hofmann, Schleif, and Zhu, 2014) for classification, and
• Median Generalized Learning Vector Quantization (Nebel, Hammer, Frohberg, and Villmann, 2015) for classification.

If you intend to use this library in academic work, please cite the respective reference paper.

Please consult the project website for more detailed information about the project.

Contents:

• Relational Neural Gas
• Relational Generalized Learning Vector Quantization
• Median Generalized Learning Vector Quantization

Indices and tables

• Index
• Module Index
• Search Page