RT info:eu-repo/semantics/article
T1 WeVoS-ViSOM: an ensemble summarization algorithm for enhanced data visualization
A1 Corchado, Emilio
A1 Baruque Zanón, Bruno
K1 Topology-preserving maps
K1 Unsupervised learning
K1 Data visualization
K1 Ensembles
K1 Summarization algorithm
K1 Informática
K1 Computer science
AB This study presents a novel version of the Visualization Induced Self-Organizing Map based on the application of a new fusion algorithm for summarizing the results of an ensemble of topology-preserving mapping models. The algorithm is referred to as Weighted Voting Superposition (WeVoS). Its main feature is the preservation of the topology of the map, in order to obtain the most accurate possible visualization of the data sets under study. To do so, a weighted voting process between the units of the maps in the ensemble takes place, in order to determine the characteristics of the units of the resulting map. Several different quality measures are applied to this novel neural architecture known as WeVoS-ViSOM and the results are analyzed, so as to present a thorough study of its capabilities. To complete the study, it has also been compared with the well-know SOM and its fusion version, with the WeVoS-SOM and with two other previously devised fusion Fusion by Euclidean Distance and Fusion by Voronoi Polygon Similarity—based on the analysis of the same quality measures in order to present a complete analysis of its capabilities. All three summarization methods were applied to three widely used data sets from the UCI Repository. A rigorous performance analysis clearly demonstrates that the novel fusion algorithm outperforms the other single and summarization methods in terms of data sets visualization
PB Elsevier
SN 0925-2312
YR 2012
FD 2012-01
LK http://hdl.handle.net/10259/3857
UL http://hdl.handle.net/10259/3857
LA eng
NO This research has been partially supported through projects CIT-020000-2008-2 and CIT-020000-2009-12 of the Spanish Ministry of Education and Innovation and project BUO06A08 of the Junta of Castilla and Leon. The authors would also like to thank the manufacturer of components for vehicle interiors, Grupo Antolin Ingenieria, S.A. within the framework of the MAGNO2008-1028 CENIT project, funded by the Spanish Ministry of Science and Innovation
DS Repositorio Institucional de la Universidad de Burgos
RD 26-abr-2024