This chapter presents a best classification of diabetes. The proposed approach work consists in two stages. In the first stage the Pima Indian diabetes dataset is obtained from the UCI repository of machine learning databases. In the second stage, the authors have performed the classification technique by using fuzzy decision tree on Pima Indian diabetes dataset. Then they applied PSO_SVM as a feature selection technique followed by the classification technique by using fuzzy decision tree on Pima Indian diabetes dataset. In this chapter, the optimization of SVM using PSO reduces the number of attributes, and hence, applying fuzzy decision tree improves the accuracy of detecting diabetes. The hybrid combinatorial method of feature selection and classification needs to be done so that the system applied is used for the classification of diabetes.
Fuzzy Decision Tree Based Classification of Psychometric Data