Improving internal-valued inferencing with Likelihod Ratio
Document Type
Article
Publication Date
1-1-2019
Abstract
This paper point out the limitations of Interval-Valued Inferencing as a defuzzification method for inference engines based on the Bandler-Kohout subproduct. As an improvement, a measurement on the likelihood of an inference result in an acceptance/rejection band suggested. With this improvement, more meaningful results are generated from a Bandler-Kohout subproduct based inference system, especially if it is implemented as a medical decision support system. To demonstrate the capability of this improvement, an experiment with a popular dataset is carried out. © 2019, Faculty of Computer Science and Information Technology.
Keywords
BK Subproduct, Defuzzification, Interval-Valued Inferencing
Divisions
fsktm
Funders
BKP Research Grant of University Malaya (Project No. BK071-2016)
Publication Title
Malaysian Journal of Computer Science
Volume
32
Issue
3
Publisher
Faculty of Computer Science and Information Technology, University of Malaya