Title :
Novel Approach to Predict Cardiovascular Disease Using Incremental SVM
Author :
Mishra, B.K. ; Lakkadwala, Prashant ; Shrivastava, N.K.
Abstract :
Now a days medical science has huge amount of data for various diagnosis of patient. With the help of data mining technique it will find out hidden information in the data. Getting medical attention early helps to take effective decision. In this paper data mining classification techniques Support Vector Machine (SVM) and Incremental SVM are analyzed on cardiovascular disease dataset. The result shows that Incremental SVM model, classify datasets based upon cardiovascular disease with less error and gives more accurate result.
Keywords :
biology computing; cardiovascular system; data mining; patient diagnosis; support vector machines; Support Vector Machine; cardiovascular disease dataset; data mining technique; incremental SVM; medical science; patient diagnosis; Cardiovascular diseases; Classification algorithms; Data mining; Heart; Support vector machines; Training; CVD; Incremental Support Vector Machine; Support Vector Machine;
Conference_Titel :
Communication Systems and Network Technologies (CSNT), 2013 International Conference on
Conference_Location :
Gwalior
Print_ISBN :
978-1-4673-5603-9
DOI :
10.1109/CSNT.2013.21