PROCEEDINGS IPMU '08
Designing Highly Interpretable Fuzzy Rule-Based Systems with Integration of Expert and Induced Knowledge
José M. Alonso, Luis Magdalena, Serge Guillaume
This work describes a new methodology
for fuzzy system modeling
focused on maximizing the interpretability
while keeping high accuracy.
In order to get a good
interpretability-accuracy trade-off,
it considers the combination of both
expert knowledge and knowledge extracted
from data. Both types of
knowledge are represented using the
fuzzy logic formalism, in the form of
linguistic variables and rules. The
integration process is made carefully
at both levels variables and rules,
avoiding contradictions and/or redundancies.
Results obtained in a
well-known benchmark classification
problem show the methodology ability
to generate highly interpretable
knowledge bases with a good accuracy,
comparable to that achieved by
other methods.
 | PDF full paper |