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Extracting decision trees from trained neural networks

DSpace at IIT Bombay

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Field Value
 
Title Extracting decision trees from trained neural networks
 
Creator KRISHNAN, R
SIVAKUMAR, G
BHATTACHARYA, P
 
Subject genetic algorithms
learning systems
data mining
knowledge based systems
 
Description In this paper we present a methodology for extracting decision trees from input data generated from trained neural networks instead of doing it directly from the data. A genetic algorithm is used to query the trained network and extract prototypes. A prototype selection mechanism is then used to select a subset of the prototypes. Finally, a standard induction method like ID3 or C5.0 is used to extract the decision tree. The extracted decision trees can be used to understand the working of the neural network besides performing classification. This method is able to extract different decision trees of high accuracy and comprehensibility from the trained neural network.
 
Publisher Elsevier
 
Date 2009-05-07T04:41:54Z
2011-12-08T06:52:31Z
2011-12-26T13:01:50Z
2011-12-27T05:47:15Z
2009-05-07T04:41:54Z
2011-12-08T06:52:31Z
2011-12-26T13:01:50Z
2011-12-27T05:47:15Z
1999
 
Type Article
 
Identifier Pattern Recognition 32(12), 1999-2009
0031-3203
10.1016/S0031-3203(98)00181-2
http://hdl.handle.net/10054/1285
http://dspace.library.iitb.ac.in/xmlui/handle/10054/1285
 
Language en