Interpretability of linguistic variables: a formal account
Ulrich Bodenhofer; Peter Bauer
Kybernetika (2005)
- Volume: 41, Issue: 2, page [227]-248
- ISSN: 0023-5954
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topBodenhofer, Ulrich, and Bauer, Peter. "Interpretability of linguistic variables: a formal account." Kybernetika 41.2 (2005): [227]-248. <http://eudml.org/doc/33751>.
@article{Bodenhofer2005,
abstract = {This contribution is concerned with the interpretability of fuzzy rule-based systems. While this property is widely considered to be a crucial one in fuzzy rule-based modeling, a more detailed formal investigation of what “interpretability” actually means is not available. So far, interpretability has most often been associated with rather heuristic assumptions about shape and mutual overlapping of fuzzy membership functions. In this paper, we attempt to approach this problem from a more general and formal point of view. First, we clarify what the different aspects of interpretability are in our opinion. Consequently, we propose an axiomatic framework for dealing with the interpretability of linguistic variables (in Zadeh’s original sense) which is underlined by examples and application aspects, such as, fuzzy systems design aid, data-driven learning and tuning, and rule base simplification.},
author = {Bodenhofer, Ulrich, Bauer, Peter},
journal = {Kybernetika},
keywords = {fuzzy modeling; interpretability; linguistic variable; machine learning; fuzzy modeling; interpretability; linguistic variable; machine learning},
language = {eng},
number = {2},
pages = {[227]-248},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Interpretability of linguistic variables: a formal account},
url = {http://eudml.org/doc/33751},
volume = {41},
year = {2005},
}
TY - JOUR
AU - Bodenhofer, Ulrich
AU - Bauer, Peter
TI - Interpretability of linguistic variables: a formal account
JO - Kybernetika
PY - 2005
PB - Institute of Information Theory and Automation AS CR
VL - 41
IS - 2
SP - [227]
EP - 248
AB - This contribution is concerned with the interpretability of fuzzy rule-based systems. While this property is widely considered to be a crucial one in fuzzy rule-based modeling, a more detailed formal investigation of what “interpretability” actually means is not available. So far, interpretability has most often been associated with rather heuristic assumptions about shape and mutual overlapping of fuzzy membership functions. In this paper, we attempt to approach this problem from a more general and formal point of view. First, we clarify what the different aspects of interpretability are in our opinion. Consequently, we propose an axiomatic framework for dealing with the interpretability of linguistic variables (in Zadeh’s original sense) which is underlined by examples and application aspects, such as, fuzzy systems design aid, data-driven learning and tuning, and rule base simplification.
LA - eng
KW - fuzzy modeling; interpretability; linguistic variable; machine learning; fuzzy modeling; interpretability; linguistic variable; machine learning
UR - http://eudml.org/doc/33751
ER -
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