Extraction of prototype-based threshold rules using neural training procedure
Date of Issue2012
International Conference on Artificial Neural Networks (22nd : 2012 : Lausanne, Switzerland)
School of Computer Engineering
Complex neural and machine learning algorithms usually lack comprehensibility. Combination of sequential covering with prototypes based on threshold neurons leads to a prototype-threshold based rule system. This kind of knowledge representation can be quite efficient, providing solutions to many classification problems with a single rule.
DRNTU::Engineering::Computer science and engineering