Abstract: This paper presents the classification technique of data mining to identify the class of an attribute with classical decision tree approach (ID3) and then to add fuzzification to improve the result of ID3. This ID3 algorithm has been implemented on weather dataset due to its easiness to use and effectiveness. ID3 algorithm is based on information gain theory and entropy values of each individual attribute. Fuzzy set theory is implemented to represent the dataset with linguistic variable and combines tree growing and cropping to determine the structure of the tree. ID3 shows better accuracy in terms of discrete value. Fuzzy logic resolves this issue for better classification on decision making. Finally fuzzification results showed more accurate classification as compared to classical decision approach.
Keywords: ID3 (Iterative Dichotomizer), Decision Tree, Fuzzy logic.
Title: Decision Making In Fuzzy Logic Environment Using ID3 Decision Tree Algorithm
Author: Nirlipta Pallabee Samapika, Aparimita Swain
International Journal of Computer Science and Information Technology Research
ISSN 2348-1196 (print), ISSN 2348-120X (online)
Research Publish Journals
