An Algorithm for Rule Extraction

To extract the rules from the information table, attribute reduction problem and attribute value reduction problem were studied. Based on rough set, a new rule extraction method was proposed. According to the indiscernible relation in rough set, discernible vector and its addition rule were defined. And meanwhile the core attribute set and the attribute reduction were obtained by scanning the information table just only one time depending on the discernible vector addition rule. Attribute value reduction was realized through gradually deleting the redundant attribute value for every rule in the information table by the correlation of condition attributes and decision attributes. Finally, a concise rule set was obtained. The illustration and experiment results indicate that the method is effective and efficient for rule extraction