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Learning Automata based Fuzzy Classifier

In this paper a fuzzy classifier based on cellular learning automata (CLA) is proposed. In the proposed classifier using a set of open asynchronous cellular learning automata, fuzzy membership functions and the rules for the fuzzy classifier are automatically generated. Each membership function is equipped with an open cellular learning automaton which is responsible for determining the best mean and variance for the corresponding membership function. In open CLA, the action of each cell in the next stage of its evolution not only depends on the local environment (actions of its neighbors) it also depends on the external environment. In order to show the performance of the proposed classifier it is tested on IRIS dataset. It is shown that using the proposed classifier, classification can be made with 8 fuzzy rules with accuracy of 97.3 % which is a good result in comparison with most of the previous methods.