Fuzzy max-min classifiers decide locally on the basis of two attributes.

Schmidt, Birka von, and Klawonn, Frank. "Fuzzy max-min classifiers decide locally on the basis of two attributes.." Mathware and Soft Computing 6.1 (1999): 91-108. <http://eudml.org/doc/39144>.

@article{Schmidt1999,
abstract = {Fuzzy classification systems differ from fuzzy controllers in the form of their outputs. For classification problems a decision between a finite number of discrete classes has to be made, whereas in fuzzy control the output domain is usually continuous, i.e. a real interval. In this paper we consider fuzzy classification systems using the max-min inference scheme and classifying an unknown datum on the basis of maximum matching, i.e. assigning it to the class appearing in the consequent of the rule whose premise fits best. We basically show that this inference scheme locally takes only two attributes (variables) into account for the classification decision.},
author = {Schmidt, Birka von, Klawonn, Frank},
journal = {Mathware and Soft Computing},
keywords = {Control difuso; Teoría de la decisión; Sistemas de control; Inferencia estadística; fuzzy control; pattern classification; max-min inference},
language = {eng},
number = {1},
pages = {91-108},
title = {Fuzzy max-min classifiers decide locally on the basis of two attributes.},
url = {http://eudml.org/doc/39144},
volume = {6},
year = {1999},
}

TY - JOUR
AU - Schmidt, Birka von
AU - Klawonn, Frank
TI - Fuzzy max-min classifiers decide locally on the basis of two attributes.
JO - Mathware and Soft Computing
PY - 1999
VL - 6
IS - 1
SP - 91
EP - 108
AB - Fuzzy classification systems differ from fuzzy controllers in the form of their outputs. For classification problems a decision between a finite number of discrete classes has to be made, whereas in fuzzy control the output domain is usually continuous, i.e. a real interval. In this paper we consider fuzzy classification systems using the max-min inference scheme and classifying an unknown datum on the basis of maximum matching, i.e. assigning it to the class appearing in the consequent of the rule whose premise fits best. We basically show that this inference scheme locally takes only two attributes (variables) into account for the classification decision.
LA - eng
KW - Control difuso; Teoría de la decisión; Sistemas de control; Inferencia estadística; fuzzy control; pattern classification; max-min inference
UR - http://eudml.org/doc/39144
ER -