Title | ||
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A novel genetic algorithm approach for simultaneous feature and classifier selection in multi classifier system |
Abstract | ||
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In this paper we introduce a novel approach for classifier and feature selection in a multi-classifier system using Genetic Algorithm (GA). Specifically, we propose a 2-part structure for each chromosome in which the first part is encoding for classifier and the second part is encoding for feature. Our structure is simple in the implementation of the crossover as well as the mutation stage of GA. We also study 8 different fitness functions for our GA based algorithm to explore the optimal fitness functions for our model. Experiments are conducted on both 14 UCI Machine Learning Repository and CLEF2009 medical image database to demonstrate the benefit of our model on reducing classification error rate. |
Year | Venue | Keywords |
---|---|---|
2014 | congress on evolutionary computation | genetic algorithm,classification error rate reduction,ga crossover stage,pattern classification,classifier selection,clef2009 medical image database,multiclassifier system,chromosome,multi-classifier system,combining rules,fitness functions,combining classifiers algorithm,genetic algorithms,tici machine learning repository,classifier fusion,ga mutation stage,feature selection |
Field | DocType | Citations |
Crossover,Pattern recognition,Feature selection,Computer science,Artificial intelligence,Margin classifier,Linear classifier,Classifier (linguistics),Genetic algorithm,Machine learning,Learning classifier system,Quadratic classifier | Conference | 9 |
PageRank | References | Authors |
0.66 | 10 | 5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Tien Thanh Nguyen | 1 | 79 | 12.55 |
Alan Wee-Chung Liew | 2 | 799 | 61.54 |
Minh Toan Tran | 3 | 20 | 1.81 |
Xuan Cuong Pham | 4 | 54 | 4.75 |
Mai Phuong Nguyen | 5 | 46 | 3.82 |