Pessimistic and Optimistic Induction

@inproceedings{Fisher1992PessimisticAO,
  title={Pessimistic and Optimistic Induction},
  author={D. Fisher},
  year={1992}
}
Learning methods vary in the optimism or pessimism with which they regard the informativeness of learned knowledge. Pessimism is implicit in hypothesis testing, where we wish to draw cautious conclusions from experimental evidence. However, this paper demonstrates that optimism in the utility of derived rules may be the preferred bias for learning systems themselves. We examine the continuum between naive pessimism and naive optimism in the context of a decision tree learner that prunes rules… CONTINUE READING

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