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Electrocardiogram Classification Based on Rough Sets and Support Vector Machine

Author: ZuoYongQiang
Tutor: MoZhiWen
School: Sichuan Normal University
Course: Applied Mathematics
Keywords: Electrocardiogram Rough Set Support Vector Machine Multi-Classes Classification Binary Tree
CLC: TP18
Type: Master's thesis
Year: 2010
Downloads: 54
Quote: 0
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Abstract


This paper studies electrocardiogram classification based on rough sets and support vector machine. First of all, it introduces the basic electrocardiogram and the theory and current application of rough sets, then review the theory and application of support vector machine based on the statistical learning theory. The weighed binary tree multi-classes classifications support vector machine is put forward at last. This paper evaluates the proposed model on T228 of Arrhythmia Database in MIT-BIH, which shows a better result compared with other methods in terms of classification speed and accuracy in the experiments.

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CLC: > Industrial Technology > Automation technology,computer technology > Automated basic theory > Artificial intelligence theory
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