Hybrid learning algorithm for fuzzy neuro systems

2005 ◽  
Author(s):  
Ching-Hung Lee ◽  
Yu-Ching Lin
Keyword(s):  
Learning Algorithm ◽  
Hybrid Learning ◽  
Hybrid Learning Algorithm

A GENETIC PROGRAMMING-BASED LEARNING ALGORITHMS FOR PRUNING COST-SENSITIVE CLASSIFIERS

2012 ◽  
Vol 11 (02) ◽  
pp. 1250011 ◽  
Author(s):  
ZAHRA NIKDEL ◽  
HAMID BEIGY
Keyword(s):  
Decision Tree ◽  
Genetic Programming ◽  
Learning Algorithm ◽  
Fitness Function ◽  
Learning Algorithms ◽  
Hybrid Learning ◽  
Experimental Results ◽  
Programming Algorithm ◽  
Hybrid Learning Algorithm ◽  
Misclassification Costs

In this paper, we introduce a new hybrid learning algorithm, called DTGP, to construct cost-sensitive classifiers. This algorithm uses a decision tree as its basic classifier and the constructed decision tree will be pruned by a genetic programming algorithm using a fitness function that is sensitive to misclassification costs. The proposed learning algorithm has been examined through six cost-sensitive problems. The experimental results show that the proposed learning algorithm outperforms in comparison to some other known learning algorithms like C4.5 or naïve Bayesian.

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