Single decision tree classifiers' accuracy on medical data

Decision tree is one of the classification techniques for classifying sequential decision problems such as those in medical domain.This paper discusses an evaluation study on different single decision tree classifiers.There are various single decision tree classifiers which have been extensively ap...

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Main Authors: Hasan, Md Rajib, Abu Bakar, Nur Azzah, Siraj, Fadzilah, Sainin, Mohd Shamrie, Hasan, Shariful
Format: Conference or Workshop Item
Language:English
Published: 2015
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Online Access:http://repo.uum.edu.my/15527/1/PID188_1.pdf
http://repo.uum.edu.my/15527/
http://www.icoci.cms.net.my/proceedings/2015/index.html
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spelling my.uum.repo.155272016-04-27T03:33:21Z http://repo.uum.edu.my/15527/ Single decision tree classifiers' accuracy on medical data Hasan, Md Rajib Abu Bakar, Nur Azzah Siraj, Fadzilah Sainin, Mohd Shamrie Hasan, Shariful QA75 Electronic computers. Computer science Decision tree is one of the classification techniques for classifying sequential decision problems such as those in medical domain.This paper discusses an evaluation study on different single decision tree classifiers.There are various single decision tree classifiers which have been extensively applied in medical decision making; each of these classifies the data with different accuracy rate.Since accuracy is crucial in medical decision making, it is important to identify a classifier with the best accuracy.The study examines the performance of fourteen single decision tree classifiers on three medical data sets, i.e. Wisconsin’s breast cancer data sets, Pima Indian diabetes data sets and hepatitis data sets.All classifiers were trained and tested using WEKA and cross validation. The results revealed that classifiers such as FT, LMT, NB tree, Random Forest and Random Tree are the five best single classifiers as they constantly provide better accuracy in their classifications. 2015-08-11 Conference or Workshop Item PeerReviewed application/pdf en http://repo.uum.edu.my/15527/1/PID188_1.pdf Hasan, Md Rajib and Abu Bakar, Nur Azzah and Siraj, Fadzilah and Sainin, Mohd Shamrie and Hasan, Shariful (2015) Single decision tree classifiers' accuracy on medical data. In: 5th International Conference on Computing and Informatics (ICOCI) 2015, 11-13 August 2015, Istanbul, Turkey. http://www.icoci.cms.net.my/proceedings/2015/index.html
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutionali Repository
url_provider http://repo.uum.edu.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Hasan, Md Rajib
Abu Bakar, Nur Azzah
Siraj, Fadzilah
Sainin, Mohd Shamrie
Hasan, Shariful
Single decision tree classifiers' accuracy on medical data
description Decision tree is one of the classification techniques for classifying sequential decision problems such as those in medical domain.This paper discusses an evaluation study on different single decision tree classifiers.There are various single decision tree classifiers which have been extensively applied in medical decision making; each of these classifies the data with different accuracy rate.Since accuracy is crucial in medical decision making, it is important to identify a classifier with the best accuracy.The study examines the performance of fourteen single decision tree classifiers on three medical data sets, i.e. Wisconsin’s breast cancer data sets, Pima Indian diabetes data sets and hepatitis data sets.All classifiers were trained and tested using WEKA and cross validation. The results revealed that classifiers such as FT, LMT, NB tree, Random Forest and Random Tree are the five best single classifiers as they constantly provide better accuracy in their classifications.
format Conference or Workshop Item
author Hasan, Md Rajib
Abu Bakar, Nur Azzah
Siraj, Fadzilah
Sainin, Mohd Shamrie
Hasan, Shariful
author_facet Hasan, Md Rajib
Abu Bakar, Nur Azzah
Siraj, Fadzilah
Sainin, Mohd Shamrie
Hasan, Shariful
author_sort Hasan, Md Rajib
title Single decision tree classifiers' accuracy on medical data
title_short Single decision tree classifiers' accuracy on medical data
title_full Single decision tree classifiers' accuracy on medical data
title_fullStr Single decision tree classifiers' accuracy on medical data
title_full_unstemmed Single decision tree classifiers' accuracy on medical data
title_sort single decision tree classifiers' accuracy on medical data
publishDate 2015
url http://repo.uum.edu.my/15527/1/PID188_1.pdf
http://repo.uum.edu.my/15527/
http://www.icoci.cms.net.my/proceedings/2015/index.html
_version_ 1644281739876499456
score 13.144533