Prediction of Heart Disease Using Multi-Layer Perceptron Neural Network and Support Vector Machine

被引：16

作者：

Nahiduzzaman, Md ^{[1
]}

Nayeem, Md Julker ^{[2
]}

Ahmed, Md Toukir ^{[3
]}

Zaman, Md Shahid Uz ^{[1
]}

机构：

[1] Rajshahi Univ Engn & Technol, Dept Elect & Comp Engn, Rajshahi, Bangladesh

[2] Pundra Univ Sci & Technol, Dept Comp Sci & Engn, Bogura, Bangladesh

[3] Bangladesh Univ, Dept Comp Sci & Engn, Dhaka, Bangladesh

来源：

2019 4TH INTERNATIONAL CONFERENCE ON ELECTRICAL INFORMATION AND COMMUNICATION TECHNOLOGY (EICT) | 2019年

关键词：

heart disease; classification; Cleveland database; multi-layer perceptron (MLP); support vector machine (SVM);

D O I：

10.1109/eict48899.2019.9068755

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In recent years, heart disease is one of the major causes of death. So it is necessary to design a system that correctly diagnoses heart disease. In this study, we have proposed two classifiers. One is a Multi-Layer Perceptron neural network (MLP) and another is Support Vector Machine (SVM). Our work is to classify two-class of heart disease and five class of heart disease. Here we have used the Cleveland heart disease online database which consists of 303 instances with 5 classes and 13 attributes. For two-class classification problem, SVM has 92.45% accuracy while the accuracy of MLP is 90.57%. For five-class classification problem, MLP has an accuracy 68.86% while SVM is 59.01%.

引用

页数：6

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