Future Prediction For Heart Attack Problem Based on Most Appropriate Attribute value

Amit Kisan Pagare, Vijay Kumar Verma

Abstract: -Superior data mining techniques are developed and used to discover hidden pattern form historical data. New Models are developed from these techniques will be useful for medical practitioners to take successful decision. Diagnosis of heart attack is a significant task in medical science. The term Heart attack includes the various diseases that involve the heart attack problem. The exposure of heart attack problem from different symptoms is an important issue for predicting heart attack problem. In this paper have taken 10 attribute which are responsible for the heart attack problem. We convert the given test data set into binary format with a possible conditions for heart attack. In seconds step we divide the data set and apply most appropriate condition on each attribute Find pair for each attribute which satisfy the condition. We repeat the process for grouping the attribute until no more grouping is possible. At last we find the most common attribute and calculate how much percentage data is accurately classified

Keywords: fitness value, heart disease, attribute, data mining, classifier