Title :
A theoretical analysis of the application of majority voting to pattern recognition
Author :
Lam, Louisa ; Suen, Ching Y.
Author_Institution :
Centre for Pattern Recognition & Machine Intelligence, Concordia Univ., Montreal, Que., Canada
Abstract :
Recently, it has been demonstrated that combining the decisions of several classifiers can lead to improved recognition results. The combination can be implemented using a variety of strategies, among which majority vote is by far the simplest, yet it has been found to be just as effective as more complicated schemes. However, all the results reported thus far on combinations of classifiers have been experimental in nature. The intention of this research is to analyze the foundations of the majority vote method in order to gain a deeper understanding and new results about its mode of operation
Keywords :
image classification; character recognition; concensus probability; image classifiers; majority voting; pattern recognition; Distributed computing; Machine intelligence; Optical character recognition software; Pattern analysis; Pattern recognition; Probability; Voting;
Conference_Titel :
Pattern Recognition, 1994. Vol. 2 - Conference B: Computer Vision & Image Processing., Proceedings of the 12th IAPR International. Conference on
Conference_Location :
Jerusalem
Print_ISBN :
0-8186-6270-0
DOI :
10.1109/ICPR.1994.576970
