Carregant...
Carregant...

Vés al contingut (premeu Retorn)

On the improvement of the mapping trustworthiness and continuity of a manifold learning model

Autor
Cruz, R.; Vellido, A.
Tipus d'activitat
Article en revista
Revista
Lecture notes in computer science
Data de publicació
2008-11
Volum
5326
Pàgina inicial
266
Pàgina final
273
DOI
https://doi.org/10.1007/978-3-540-88906-9_34 Obrir en finestra nova
Repositori
http://hdl.handle.net/2117/13071 Obrir en finestra nova
Resum
Manifold learningmethodsmodel high-dimensional data through low-dimensional manifolds embedded in the observed data space. This simplification implies that their are prone to trustworthiness and continuity errors. Generative Topographic Mapping (GTM) is one such manifold learning method for multivariate data clustering and visualization, defined within a probabilistic framework. In the original formulation,GTMis optimized byminimization of an error that is a function of Euclidean distances, maki...
Citació
Cruz, R.; Vellido, A. On the improvement of the mapping trustworthiness and continuity of a manifold learning model. "Lecture notes in computer science", Novembre 2008, vol. 5326, p. 266-273.
Grup de recerca
IDEAI-UPC Intelligent Data Science and Artificial Intelligence
SOCO - Soft Computing

Participants