Evaluation of Clustering Techniques in Data Mining Tools
نویسندگان
چکیده
Clustering divides a heterogeneous population into a number of more homogeneous subgroups or clusters to reflect the segments in a dataset such that patterns can be recognized. This research shows how a software evaluation framework may be adapted to evaluate commercial data mining tools for a specific user environment. We applied this adaptation to evaluate two major commercial data mining tools, SAS Enterprise Miner (EM) and IBM DB2 Intelligent Miner (IM), for use in a university environment.
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تاریخ انتشار 2004