Distributed Nearest Neighbor-Based Condensation of Very Large Data Sets

In this work, the parallel fast condensed nearest neighbor (PFCNN) rule, a distributed method for computing a consistent subset of a very large data set for the nearest neighbor classification rule is presented. In order to cope with the communication overhead typical of distributed environments and...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE transactions on knowledge and data engineering Jg. 19; H. 12; S. 1593 - 1606
Hauptverfasser:	Angiulli, F., Folino, G.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.12.2007 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithm design and analysis Algorithms and association rules Cellular neural networks Classification Clustering Collection Computation Concurrent computing Condensing Cost analysis Costs Data mining Data reduction Distributed algorithms Distributed computing Distributed systems Grid computing Nearest neighbor searches Neural networks Clustering classification Data mining Distributed systems and association rules
ISSN:	1041-4347, 1558-2191
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!