Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Handwritten numerical recognition based on multiple algorithms
Pattern Recognition
Original Contribution: Stacked generalization
Neural Networks
Decision Combination in Multiple Classifier Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Combining the results of several neural network classifiers
Neural Networks
A Method of Combining Multiple Experts for the Recognition of Unconstrained Handwritten Numerals
IEEE Transactions on Pattern Analysis and Machine Intelligence
A multistage generalization of the rank nearest neighbor classification rule
Pattern Recognition Letters
Optimal combinations of pattern classifiers
Pattern Recognition Letters
Image sampling rate and image pattern recognition
Image sampling rate and image pattern recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple network fusion using fuzzy logic
IEEE Transactions on Neural Networks
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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.