Probabilistic and fuzzy methods for information fusion in data mining
Nicholas J. Randon, Jonathan Lawry · International Journal of Intelligent Systems · 2003
With the wealth of information available in the world today the challenge of how to extract information from several data sources in an intuitive and transparent manner has emerged in machine learning. This article describes a method for learning models from a database using linguistic descriptions on fuzzy sets and fusion methods in a data-mining framework. It focuses on AND/OR combination functions and shows how these can be optimized for knowledge extraction and classification of data. © 2003 Wiley Periodicals, Inc.