A KDD System for the Discovery of Quantified Exception Rules

The goal of KDD is broader and it is always interesting to discover exceptions, as they challenge the existing knowledge and often lead to the growth of knowledge in new directions. In proposed work a KDD system has been presented for the discovery of knowledge base which is a collection of quantified exception rules in the form of P ¿ D unless C: ¿, ß, ¿ , ¿ Where ¿, ß, ¿ , ¿ are quantified values associated with each exception rule. Dempster Shafer theory has been used for uncertainty quantification. Experimental results are given to support the proposed KDD System, which was quite encouraging.