In this paper two techniques to project high dimensional data into a bidimensional space are introduced. These techniques are based on an unsupervised neural network of enhanced processing elements. The proposed approaches are compared with some widely known projection techniques based on unsupervised neural networks. These comparisons show that the new projection techniques perform comparably or slightly better than the traditional techniques and are promising in term of computational burden.
Multivariate Data Projection Techniques Based on a Network of Enhanced Neural Elements / Acciani, G.; Chiarantoni, Ernesto; Minenna, M.; Vacca, Francesco. - STAMPA. - (1996), pp. 211-216. (Intervento presentato al convegno InternationaI Conference on Neural Networks, ICNN 1996 tenutosi a Washington, DC nel June 3-6,1996) [10.1109/ICNN.1996.548893].
Multivariate Data Projection Techniques Based on a Network of Enhanced Neural Elements
Acciani, G.;CHIARANTONI, Ernesto;Vacca, Francesco
1996-01-01
Abstract
In this paper two techniques to project high dimensional data into a bidimensional space are introduced. These techniques are based on an unsupervised neural network of enhanced processing elements. The proposed approaches are compared with some widely known projection techniques based on unsupervised neural networks. These comparisons show that the new projection techniques perform comparably or slightly better than the traditional techniques and are promising in term of computational burden.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
