This paper investigates scalable implementations of out-of-core I/O-intensive Data Mining algorithms on affordable parallel architectures, such as clusters of workstations. In order to validate our approach, the K-means algorithm, a well known DM Clustering algorithm, was used as a test case.
|Data di pubblicazione:||2000|
|Titolo:||Implementation Issues in the Design of I/O Intensive Data Mining Applications on Clusters of Workstations|
|Rivista:||LECTURE NOTES IN COMPUTER SCIENCE|
|Appare nelle tipologie:||2.1 Articolo su rivista |