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A theoretical study on six classifier fusion strategies
2002
IEEE Transactions on Pattern Analysis and Machine Intelligence
We look at a single point in the feature space, two classes, and L classifiers estimating the posterior probability for class ! 1 . Assuming that the estimates are independent and identically distributed (normal or uniform), we give formulas for the classification error for the following fusion methods: average, minimum, maximum, median, majority vote, and oracle.
doi:10.1109/34.982906
fatcat:4jaicjswjrfmlk3q4nitfwdc5a