A Study on Analysis of Various Datamining Classification Techniques on Healthcare Data

-The health care industry is one of the world’s largest and fastest growing industries having huge amount of healthcare data. This health care data includes relevant information about patient data, their treatment data and resource management data. The information is rich and massive. Hidden relationships and trends in healthcare data can be discovered from the application of data mining techniques. Data mining techniques are more effective that has used in healthcare research. In this paper we aimed to do the analysis of several data mining classification techniques using WEKA machine learning tools over the healthcare datasets. In this study, we use different data mining classification techniques that have been tested on two heart disease datasets. The standards used are percentage of accuracy and error rate of every applied classification technique. The technique which is suitable for a particular dataset is chosen based on highest classification accuracy rate and least error rate. Keywords--Classification technique, Machine Learning Tools, Heart disease, Data Mining, Healthcare, KDD