On combining classifiers using sum and product rules

Pattern Recognition Letters

Volumn 22, Issue 12, 2001, Pages 1283-1289

  Alexandre, Luís A ^a,b   Campilho, Aurélio C ^a,c   Kamel, Mohamed ^d  

^a INEB INSTITUTO DE ENGENHARIA BIOMÉDICA   (Portugal)

^b UNIVERSITY OF BEIRA INTERIOR   (Portugal)

^c UNIVERSITY OF PORTO   (Portugal)

^d UNIVERSITY OF WATERLOO   (Canada)

Author keywords

Classification; Classifier fusion; Combining classifiers; K nearest neighbours; Neural networks

Indexed keywords

COMBINATORIAL MATHEMATICS; EQUIVALENCE CLASSES; ESTIMATION; PROBABILITY;

MULTIPLE CLASSIFIERS;

PATTERN RECOGNITION;

ARTIFICIAL NEURAL NETWORK;

EID: 0034875843     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0167-8655(01)00073-3     Document Type: Article

References (13)

1. Combining independent and unbiased classifiers using weighted average
2. Neural network ensembles
3. Optimal linear combinations of neural networks
4. Combining classifiers
5. On combining classifiers
6. Popular ensemble methods: An empirical study
7. Neural network classifiers estimate Bayesian a posteriori probabilities
8. Combining the results of several neural network classifiers
9. Comparison between product and mean classifier combination rules
10. Optimal linear combination of neural networks for improving classification performance