Decision making in eye cataract by using mamdani fuzzy inference system

This paper presents on the classification technique of data mining to identify the class of an attribute with classical decision tree approach and then to add fuzzification to improve the result of decision tree. It has been implemented on an eye disease i.e. cataract dataset. Fuzzy set theory implemented to represent the dataset with linguistic variable combines tree growing and cropping to determine the structure of the tree. It shows better accuracy in terms of discrete value not for continues. Fuzzy logic resolves this issue for better classification on decision making. Finally classification results showed more accurate classification as compare to classical decision approach.