Research and application of clustering algorithm for arbitrary data set

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Research and application of clustering algorithm for arbitrary data set
Συγγραφείς: Song, Yu-Chen, O'Grady, Michael J., O'Hare, G. M. P. (Greg M. P.)
Στοιχεία εκδότη: IEEE Computer Society
Έτος έκδοσης: 2009
Συλλογή: University College Dublin: Research Repository UCD
Θεματικοί όροι: Cluster analysis--Computer programs, Algorithms
Περιγραφή: Paper presented at the 2008 International Conference on Computer Science and Software Engineering, December 12-14, 2008, Wuhan, China ; This paper discusses the theory and algorithmic design of the CADD (clustering algorithm based on object density and direction) algorithm. This algorithm seeks to harness the respective advantages of the k-means and DENCLUE algorithms. Clustering results are illustrated using both a simple data set and one from the geological domain. Results indicate that CADD is robust in that automatically determines the number K of clusters, and is capable of identifying clusters of multiple shapes and sizes. ; Science Foundation Ireland ; Conference details ; http://www.highsci.org/csse2008submission/website/csse/index.aspx
Τύπος εγγράφου: conference object
Περιγραφή αρχείου: 457320 bytes; application/pdf
Γλώσσα: English
ISBN: 978-0-7695-3336-0
0-7695-3336-1
Relation: Proceedings : International Conference on Computer Science and Software Engineering : CSSE 2008 : Volume 04; http://hdl.handle.net/10197/1347
DOI: 10.1109/CSSE.2008.415
Διαθεσιμότητα: http://hdl.handle.net/10197/1347
https://doi.org/10.1109/CSSE.2008.415
Αριθμός Καταχώρησης: edsbas.170FD3EF
Βάση Δεδομένων: BASE
Περιγραφή
ISBN:9780769533360
0769533361
DOI:10.1109/CSSE.2008.415