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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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