Mistake Bound Framework(出错界限模型)

Mistake Bound Framework(出错界限模型)

Mistake Bound Framework

  • So far: how many examples needed?

  • What about: how many mistakes before convergence?

  • Let’s consider similar setting to PAC learning:

  • Instances drawn at random from X according to distribution D
  • Learner must classify each instance before receiving correct
    classification from teacher
  • Can we bound the number of mistakes learner makes before
    converging?
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