Comparative Study of Bayes Net and Multilayer Perceptron Model using ECG Signals

Authors

  • S. Monica Department of Computer Science Engineering, AVS College of Arts and Science, Salem (DT), Tamilnadu, India

DOI:

https://doi.org/10.37591/rtpc.v2i2.513

Abstract

In recent days, heart abnormalities are common among people regardless of their age. Heart abnormalities must be detected and treated in very initial stage which protects people from major heart abnormalities. Sometimes, physician feels difficulty in classifying heart abnormalities from extracted features. This problem can be solved with an excellent data mining technique called classification. Classification is a data mining technique which is used to label tuples. In this paper we compare the accuracy of two classifiers namely Bayes net classifier and multi layer Perceptron classifier. PTB database is used for classification which is done in weka.

Keywords: ECG Signals, Bayes net, PTB database

 

Cite this Article
S. Monica. Comparative study of Bayes Net and Multilayer Perceptron model using ECG Signals. Recent Trends in Parallel Computing. 2015; 2(2): 14–17p.

References

http://www.cardionetics.com/sinus-node-disease

http://www.physionet.org

http://en.wikipedia.org/wiki/Electrocardiography

http://www.southsudanmedicaljournal.com/archive/may-2010/howto-read-an-electrocardiogram-ecg.-part-one-basic-principles-of-theecg.-the-normal-ecg.html

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Published

2015-08-12

Issue

Vol. 2 No. 2 (2015)

Section

Review Articles

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