Clustering of interval-valued data using adaptive squared Euclidean distances

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3316, Issue , 2004, Pages 775-780

  De Souza, Renata M C R ^a   De Carvalho, Francisco De A T ^a   Silva, Fabio C D ^a  

^a FEDERAL UNIVERSITY OF PERNAMBUCO   (Brazil)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTERS;

ADAPTIVE VERSIONS; ADEQUACY CRITERION; CLUSTERING METHODS; DYNAMIC CLUSTER ALGORITHMS; INTERVAL-VALUED DATA; SQUARED EUCLIDEAN DISTANCE;

ALGORITHMS;

EID: 35048881069     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-30499-9_119     Document Type: Article

References (5)

1. Bock, H.H. and Diday, E.: Analysis of Symbolic Data: Exploratory Methods for Extracting Statistical Information from Complex Data. Springer, Berlin Heidelberg (2000)
2. De Carvalho, F. A. T. Brito, P. and Bock H. H., Dynamical Clustering for symbolic quantitative data. In: Workshop in Symbolic Data Analysis, Cracow, (2002)
3. Diday, E. and Govaert, G.: Classification Automatique avec Distances Adaptatives. R.A.I.R.O. Informatique Computer Science, 11 (4) (1977) 329-349
4. Hubert, L. and Arabie, P.: Comparing Partitions. Journal of Classification, 2 (1985) 193-218
5. Souza, R.M.C.R. and De Carvalho, F. A. T.: Clustering of interval data based on city-block distances. Pattern Recognition Letters, 25 (3) (2004) 353-365