Clustering of symbolic data using the assignment-prototype algorithm
Silva, K.P.; De A. T. De Carvalho, Francisco; Csernel, Marc (2009-06), Clustering of symbolic data using the assignment-prototype algorithm, International Joint Conference on Neural Networks, 2009. IJCNN 2009. Proceedings, IEEE : Piscataway, NJ, p. 2936-2942. http://dx.doi.org/10.1109/IJCNN.2009.5178764
TypeCommunication / Conférence
Conference titleInternational Joint Conference on Neural Networks, 2009. IJCNN 2009
Book titleInternational Joint Conference on Neural Networks, 2009. IJCNN 2009. Proceedings
MetadataShow full item record
Abstract (EN)This paper shows a fuzzy relational clustering method in order to perform the clustering of symbolic data. The presented method yields a fuzzy partition and prototype for each cluster by optimizing an adequacy criterion based on suitable dissimilarity measures. This work considers two volume-based measures that may be applied to data described by set-valued, list-valued or interval-valued symbolic variables. Experiments with real and synthetic symbolic data sets show the usefulness of the proposed approach. The accuracy of the results were assessed by the corrected Rand index and the overall error rate of classification.
Subjects / KeywordsAlgorithmes; Classification automatique; Analyse des données symboliques; clustering methods
Showing items related by title and author.
Carvalho, Francisco de A.T. de; Bertrand, Patrice; Simões, Eduardo C. (2016) Article accepté pour publication ou publié