Knowledge-oriented clustering for decision support

Cluster analysis is traditionally an unsupervised data. reduction technique. However, by unifying ideas from both cluster analysis and rough set theory, the inherent structure of a data set can be expressed as a rule set which, in turn, can be modified in a supervised manner to obtain a decision rule set with minimal ambiguity. This process of encasing knowledge extraction in an algorithmic framework results in an optimal process for decision support.