@inproceedings{bbdeb07c5aac4cf394b6232c27bd3f4d,
title = "Confidence combination methods in multi-expert systems",
abstract = "In the proposed paper, we investigate the combination of the multi-expert system in which each expert outputs a class label as well as a corresponding confidence measure. We create a special confidence measurement which is common for all experts and use it as a basis for the combination. We develop three combination methods. The first method is theoretically optimal but requires very large representative training data and storage memory for look-up table. It is actually impractical. The second method is suboptimal and reduces greatly the required training data and memory space. The last method is a simplified version of the second and needs the least training data and memory space. All three methods demand no mutual independence of the experts, thus should be useful in many applications.",
keywords = "Bayes rule, Classifier, Combination methods, Confidences, Expert, OCR",
author = "Yingquan Wu and K. Ianakiev and V. Govindaraju",
year = "2000",
doi = "10.1007/3-540-44522-6\_66",
language = "English",
isbn = "3540679464",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "641--649",
editor = "Ferri, \{Francesc J.\} and Inesta, \{Jose M.\} and Adnan Amin and Pavel Pudil",
booktitle = "Advances in Pattern Recognition - Joint IAPR International Workshops, SSPR 2000 and SPR 2000, Proceedings",
address = "Germany",
note = "8th Meeting of the International Workshop on Structural and Syntactic Pattern Recognition, SSPR 2000 and 3rd International Workshop on Statistical Techniques in Pattern Recognition, SPR 2000 ; Conference date: 30-08-2000 Through 01-09-2000",
}