Application of the confidence measure in knowledge acquisition process

Authors:
Michal Wozniak
Affiliations:
Chair of Systems and Computer Networks, Wroclaw University of Technology, Poland and The Higher Vocational State School in Legnica, Poland
Venue:
ICCS'03 Proceedings of the 2003 international conference on Computational science: PartIII
Year:
2003

Citing 6
Cited 1

Rule-based systems and pattern recognition

Pattern Recognition Letters
Probabilistic reasoning in intelligent systems: networks of plausible inference

Probabilistic reasoning in intelligent systems: networks of plausible inference
Machine Learning

Machine Learning
Comparative Performance of Rule Quality Measures in an InductionSystem

Applied Intelligence
Induction of Rules Subject to a Quality Constraint: Probabilistic Inductive Learning

IEEE Transactions on Knowledge and Data Engineering
Pattern Classification (2nd Edition)

Pattern Classification (2nd Edition)

Proposition of common classifier construction for pattern recognition with context task

Knowledge-Based Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

Paper deals with the knowledge acquisition process. Different experts formulate the rules for decision support systems. We assume they have different knowledge about the problem and therefore obtained rules have different qualities. We will formulate the proposition of the confidence measure and its application to the decision process based on Bayes formulae. We will propose how calculate the value of measure under consideration for typical statistical learning process. On the base on the proposed measure of the knowledge quality we propose the procedure of the contradictions elimination for the set of logical rules.