A theoretical study on six classifier fusion strategies

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Abstract

We look at a single point in feature space, two classes, and L classifiers estimating the posterior probability for class /spl omega//sub 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.

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Cite This Study

Ludmila I. Kuncheva (Tue,) studied this question.

synapsesocial.com/papers/6986594c13009c295e2f0fc4 https://doi.org/https://doi.org/10.1109/34.982906

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Journals

IEEE Transactions on Pattern Analysis and Machine Intelligence

Institutions

University of Wales

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