Open AccessConfidence-based voting procedure for combining fuzzy systems and neural networks
Author(s) -
Vladimir Stanovov,
Ш А Ахмедова,
Yukihiro Kamiya
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/734/1/012087
Subject(s) - artificial intelligence , computer science , artificial neural network , fuzzy logic , voting , classifier (uml) , machine learning , data mining , neuro fuzzy , pattern recognition (psychology) , fuzzy control system , politics , political science , law
In this study the confidence-based voting of neural net classifier and fuzzy logic based classifiers is proposed. In this method, for the cases when the fuzzy system is confident enough in its decision, i.e. when the membership value is large enough, fuzzy system makes the decision, otherwise, the neural net is applied. This allows classifying most of the objects by explainable interpretable fuzzy system, while using the more accurate neural network for the most difficult cases. The experiments are performed on a set of test datasets, and two problems of identifying the emotional state of a person using the data collected by non-contact vital Doppler sensors. The results show that this setup allows not only improving the classification quality, but also allows to explain the classification process the explanation of the classifier functioning.