Trustworthiness evaluation and retrieval-based revision method for case-based reasoning classifiers. Issue 21 (30th November 2015)

• Record Type: Journal Article
• Authors: Yan, Aijun; Wang, Dianhui
• Is Part Of: Expert systems with applications. Volume 42:Issue 21(2015)
• Page Start: 8006
• Page End: 8013
• Publication Date: 2015-11-30
• Subjects: Case-based reasoning classifiers -- Classification accuracy -- Case evaluation -- Case revision; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2015.06.027
• Languages: English
• ISSNs: 0957-4174

Abstract

Abstract: To achieve better classification performance using case-based reasoning classifiers, we propose a retrieval-based revision method with trustworthiness evaluation for problem solving. An improved case evaluation method is employed to evaluate the trustworthiness of the suggested solution after the reuse step, which will divide the target cases and its suggested solutions into a trustworthy set and an untrustworthy set in accordance with a threshold value of trustworthiness. The attribute weights are adjusted by running a genetic algorithm and are used in the second round of retrieval of the untrustworthy set to obtain the classification results. Experimental results demonstrate that our proposed method performs favorably compared with other methods. Also, the proposed method has less computation complexity for the trustworthiness evaluation, and enhances understanding on thinking and inference for case-based reasoning classifiers.