Performance Analysis of Various Data Mining Classification Techniques on Healthcare Data

Health care data includes patient centric data, their treatment data and resource management data. It is very massive and information rich. Valuable knowledge i.e. hidden relationships and trends in data can be discovered from the application of data mining techniques on healthcare data. Data mining techniques have been used in healthcare research and known to be effective. The present study aimed to do the performance analysis of several data mining classification techniques using three different machine learning tools over the healthcare datasets. In this study, different data mining classification techniques have been tested on four different healthcare datasets. The standards used are percentage of accuracy and error rate of every applied classification technique. The experiments are done using the 10 fold cross validation method. A suitable technique for a particular dataset is chosen based on highest classification accuracy and least error rate.