Analysis of Data Mining Classification Techniques

Data Mining offers wide range of approaches for extracting information from data. In the medical area, data mining may be utilised to anticipate diagnoses sooner and with more consistent and reliable findings by evaluating the massive amounts of data accessible. In this paper, WEKA (Waikato Environment for Knowledge Analysis) is used which is a toolkit of machine learning algorithms for tasks of data mining. WEKA is a visualization tool that comprises a variety of tools and algorithms such as Naive Bayes, Decision tree, Multilayer Perceptron and j48 classifier for addressing real-world data mining issues and assisting in forecasting. In this work, Pima Indians Diabetes Database is utilized which is gathered from National Institute of Diabetes and Digestive and Kidney Diseases for classification to enhance precision, recall, f-measurement, and accuracy.