A new rule space representation scheme for rule induction in classification and control applications

作者：Bigot S^*

来源：Proceedings of the Institution of Mechanical Engineers Part I-Journal of Systems and Control Engineering, 2011, 225(I7): 1018-1038.

DOI：10.1177/0959651810396292

• rule induction
• fuzzy system
• concept learning
• search strategy
• classification
• control

Over the past few decades, several covering algorithms have been developed to automate the acquisition of knowledge from a set of examples. These algorithms employ a specific search process for extracting IF-THEN rules. They rely heavily on statistical measures to guide the search for rules; however, the information carried by these measures is limited and does not always lead to the best results. This paper presents two new algorithms which employ a new knowledge representation scheme to optimize the search and reduce the role of statistical measures, namely RULES-5 Plus for classification problems (discrete outputs) and RULES-F Plus for control applications (numerical outputs).

• 出版日期2011-11