ugtm: A Python Package for Data Modeling and Visualization Using Generative Topographic Mapping

ugtm is a Python package that implements generative topographic mapping (GTM), a dimensionality reduction algorithm by Bishop, Svensén and Williams. Because of its probabilistic framework, GTM can also be used to build classification and regression models, and is an attractive alternative to t-distr...

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Bibliographic Details
Published inJournal of open research software Vol. 6; no. 1; p. 26
Main Author Gaspar, Héléna Alexandra
Format Journal Article
LanguageEnglish
Published Ubiquity Press Ltd 19.12.2018
Ubiquity Press
Subjects
Algorithms
classification
data analysis
data visualization
dimensionality reduction
generative topographic mapping
machine learning
regression
Technology application
Topography
Online AccessGet full text
ISSN2049-9647
2049-9647
DOI10.5334/jors.235

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Summary:ugtm is a Python package that implements generative topographic mapping (GTM), a dimensionality reduction algorithm by Bishop, Svensén and Williams. Because of its probabilistic framework, GTM can also be used to build classification and regression models, and is an attractive alternative to t-distributed neighbour embedding (t-SNE) or other non-linear dimensionality reduction methods. The package is compatible with scikit-learn, and includes a GTM transformer (eGTM), a GTM classifier (eGTC) and a GTM regressor (eGTR). The input and output of these functions are numpy arrays. The package implements supplementary functions for GTM visualization and kernel GTM (kGTM). The code is under MIT license and available on GitHub (
ISSN:2049-9647
2049-9647
DOI:10.5334/jors.235