DocumentCode :
3274361
Title :
Study on classification rules of hypertension based on decision tree
Author :
Zhang Wei ; Zhang Xuan ; Chen Junjie
Author_Institution :
Inf. Center, Shanxi Med. Coll. for Continuing Educ., Taiyuan, China
fYear :
2013
fDate :
23-25 May 2013
Firstpage :
93
Lastpage :
96
Abstract :
To extract classification rules of hypertension more effectively, the C4.5 decision tree algorithm was put forward. Firstly, C4.5 algorithm was used to analyse pre-processed hypertension data and a decision tree model was constructed. Then, the understandable classification rules were extracted and the maintaining method was used to test the accuracy of the classification results. Finally, the improved C4.5 algorithm was proposed to amend the information gain of the selected attribute by introducing the concept of correlation. The improved decision tree model more conforms to the medical understanding and the classification accuracy was also improved. The experiment results show that the improved algorithm was effective.
Keywords :
data analysis; data mining; decision trees; medical diagnostic computing; pattern classification; C4.5 decision tree algorithm; classification accuracy; correlation concept; hypertension classification rules; hypertension data analysis; information gain; maintaining method; medical understanding; understandable classification rules; Accuracy; Education; Hardware design languages; Hypertension; Standards; Sugar; Terminology; correlation; data mining; decision tree; hypertension;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Engineering and Service Science (ICSESS), 2013 4th IEEE International Conference on
Conference_Location :
Beijing
ISSN :
2327-0586
Print_ISBN :
978-1-4673-4997-0
Type :
conf
DOI :
10.1109/ICSESS.2013.6615263
Filename :
6615263
Link To Document :
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