Experts' Boasting in Trainable Fusion Rules

  title={Experts' Boasting in Trainable Fusion Rules},
  author={Sarunas Raudys},
  journal={IEEE Trans. Pattern Anal. Mach. Intell.},
We consider the trainable fusion rule design problem when the expert classifiers provide crisp outputs and the behavior space knowledge method is used to fuse local experts’ decisions. If the training set is utilized to design both the experts and the fusion rule, the experts’ outputs become too self-assured. In small sample situations, “optimistically biased” experts’ outputs bluffs the fusion rule designer. If the experts differ in complexity and in classification performance, then the… CONTINUE READING

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