Classification of Biochemical and Biomechanical Data of Diabetic Rats Treated with Magnetic Field By PCA-Supported J48 Algorithm

The aim of this study was to investigate the J48 mediated decision tree algorithm from the principal component analysis - PCA, which is more complex, one of the statistical algorithms of diabetic metabolic disorders of Wistar albino rats' biochemical values and magnetic field application. Wistar Albino rats were examined under 4 different groups including the control group. When the results were examined, it was observed that PCA increased the success rate of classification from 96.25% to 97.50% when used with J48 decision tree algorithm. Thus, the PCA-supported J48 algorithm demonstrated that Wistar albino rats could be successfully used on the data obtained from more complex diabetic metabolic values.