COMPARISON OF DIFFERENT CLASSIFICATION ALGORITHMS FOR A DIABETES DATASET USING WEKA

Аннотация

Data mining relies upon compiling information assortment, warehousing and computer processing. This paper analyses the various algorithms used in machine learning system. It analyses and interprets the results based on the classification of a single data set using various classification techniques. The dataset used in this paper relates to Diabetes. The algorithms used in this paper are logical regression, Random Forest Algorithm and JRip. The data set is taken from UCI ML repository and it relates to the population of effected diabetic patients in India in which mostly population are young females in their early twenties.