Efficient classification and analysis of Ischemic Heart Disease using Proximal Support Vector Machines based Decision Trees

被引：2
|
作者：
Soman, KP [1 ]
Shyman, MD [1 ]
Madhavdas, P [1 ]
机构：
[1] Amrita Univ, Amrita Vishwa Vidyapeetham, CEN, Coimbatore 6411105, Tamil Nadu, India
来源：
IEEE TENCON 2003: CONFERENCE ON CONVERGENT TECHNOLOGIES FOR THE ASIA-PACIFIC REGION, VOLS 1-4 | 2003年
关键词：
D O I：
10.1109/TENCON.2003.1273317
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Ischemic heart disease (IHD) is one of the toughest challenges to doctors in making right decisions due to its skimpy symptoms and complexity. We have analyzed IHD data from 65 patients to provide an aid for decision-making. Decision trees give potent structural information about the data and thereby serve as a powerful data mining tool. Support Vector Machines serve as excellent classifiers and predictors and can do so with high accuracy. Our tree based classifier uses non-linear proximal support vector machines (PSVM). The accuracy is very high (100% for training data) and the tree is small and precise.
引用
收藏
页码：214 / 217
页数：4
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