Anbananthen, S. Kalaiarasi and Sainarayanan , Gopala and Ali Chekima, and Teo, Jason Tze Wi (2005) DATA mining using artificial neural network tree. In: 2005 1st International Conference on Computers, Communications and Signal Processing with Special Track on Biomedical Engineering, CCSP 2005, 14-16 November 2005, Kuala Lumpur.
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Official URL: http://dx.doi.org/10.1109/CCSP.2005.4977180
Proper diagnosis, classification and prediction of diabetes are essential due to the increasing prevalence ofthe disease and the increasing cost to control it. Appropriate discovery ofknowledge from historical data for this disease would be a valuable tool for clinical researchers. The main purpose of data mining is to gain insight ofthe data, and extract knowledge (inter-relational patterns) from the data. Applying data mining techniques in diabetic data can facilitate systematic analysis. Artificial Neural network (ANN) has already been applied in a variety ofdomains with remarkable success. However, it has not has been well utilized in data mining because of he "black box" nature. In this paper we present a method of using ANN in data mining and overcoming the "black box" nature using Decision Tree.
|Item Type:||Conference Paper (UNSPECIFIED)|
|Uncontrolled Keywords:||Data mining, Decision tree, Diabetes, Neural network, Rule extraction|
|Subjects:||?? R855-855.5 ??|
?? QA75.5-76.95 ??
|Divisions:||SCHOOL > School of Engineering and Information Technology|
|Deposited By:||IR Admin|
|Deposited On:||10 Feb 2012 14:38|
|Last Modified:||29 Dec 2014 16:19|
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