Implementation Issues in the Design of I/O Intensive Data Mining Applications on Clusters of Workstations
نویسندگان
چکیده
This paper investigates scalable implementations of out-ofcore I/O-intensive Data Mining algorithms on a ordable 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.
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