



@article {2542,
	title = {On combining classifiers using sum and product rules},
	journal = {Pattern Recognition LettersPattern Recogn. Lett.},
	volume = {22},
	year = {2001},
	note = {Cited By (since 1996): 51Export Date: 21 November 2012Source: Scopusdoi: 10.1016/S0167-8655(01)00073-3Language of Original Document: EnglishCorrespondence Address: Alexandre, L.A.; INEB-Inst. de Engenharia Biomedica, Rua Dr. Roberto Frias s/n, Porto 4200-465, Portugal; email: lfbaa@noe.ubi.ptReferences: Alexandre, L., Campilho, A., Kamel, M., Combining independent and unbiased classifiers using weighted average (2000) Proc. 15th Internat. Conf. on Pattern Recognition, 2. , IEEE Press, Barcelona, Spain;Bishop, C., (1995) Neural Networks for Pattern Recognition, , Oxford University Press, Oxford; 
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},
	month = {2001///},
	pages = {1283 - 1289},
	abstract = {This paper presents a comparative study of the performance of arithmetic and geometric means as rules to combine multiple classifiers. For problems with two classes, we prove that these combination rules are equivalent when using two classifiers and the sum of the estimates of the a posteriori probabilities is equal to one. We also prove that the case of a two class problem and a combination of two classifiers is the only one where such equivalence occurs. We present experiments illustrating the equivalence of the rules under the above mentioned assumptions. {\textcopyright} 2001 Elsevier Science B.V. All rights reserved.},
	keywords = {artificial neural network, Classification, Classifier fusion, Combinatorial mathematics, Combining classifiers, Equivalence classes, Estimation, K nearest-neighbours, Multiple classifiers, Neural networks, Pattern recognition, probability},
	isbn = {01678655 (ISSN)},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0034875843\&partnerID=40\&md5=becfe9c0c4a7d97f7bbaf33f3059ef8f},
	author = {Alexandre, L.A. and Campilho, A.C. and Kamel, M.}
}
