Comparing and evaluating the performance of WEKA classifiers on critical diseases

Cancer, Cardiovascular diseases and Diabetes are the leading causes of death worldwide. The Classification and Characterization for the treatment strategies are essential for these critical diseases. Data mining have been used in real time applications due to its artificial intelligence nature. It is highly used in medical domain as it helps in better predictions and supports in decision making. This paper analyses the medical data using data mining technique called WEKA. Some data mining classification algorithms (like J48, naïve-bayes and random-forest) are implemented on the dataset.