Sensitivity Analysis and Prediction of Optimal Rules for Medical Data by Using Rough Set Theory

  • N. Divya, V. V. S. S. S. Balaram

Abstract

The data mining techniques-based systems could have a crucial impact on the employees’ lifestyle to predict heart diseases. There are many scientific papers, which use the techniques of data mining to predict heart diseases. However, limited scientific papers have addressed the four cross-validation techniques of splitting the data set that plays an important role in selecting the best technique for predicting heart disease. It is important to choose the optimal combination between the cross-validation techniques and the data mining, classification techniques that can enhance the performance of the prediction models.the growing research on heart disease predicting system, it has become important to categories the research outcomes and provides readers with an overview of the existing heart disease prediction techniques in each category. Neural Networks are one of many data mining analytical tools that can be utilized to make predictions for medical data. From the study it is observed that Hybrid Intelligent Algorithm improves the accuracy of the heart disease prediction system.

Published
2019-09-29
How to Cite
N. Divya, V. V. S. S. S. Balaram. (2019). Sensitivity Analysis and Prediction of Optimal Rules for Medical Data by Using Rough Set Theory. International Journal of Advanced Science and Technology, 28(7), 526 - 535. Retrieved from http://sersc.org/journals/index.php/IJAST/article/view/37706
Section
Articles