Analyzing Data Clusters: A Rough Sets Approach to Extract Cluster-Defining Symbolic Rules
نویسندگان
چکیده
In this paper we present a strategy together with its computational implementation to intelligently analyze data clusters in terms of symbolic cluster-defining rules. We present a symbolic rule extraction workbench that leverages rough set theory to inductively extract CNF form symbolic rules from un-annotated continuous-valued data-vectors. Our workbench purports a hybrid rule extraction methodology, incorporating a sequence of methods to achieve data clustering, data discretization and eventually symbolic rule discovery via rough set approximation. The featured symbolic rule extraction workbench will be tested and analyzed using several well-known biomedical datasets.
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