Boosting Using Branching Programs

  title={Boosting Using Branching Programs},
  author={Yishay Mansour and David A. McAllester},
  journal={J. Comput. Syst. Sci.},
It is known that decision tree learning can be viewed as a form of boosting. Given a weak learning hypothesis one can show that the training error of a decision tree declines as |T| where |T| is the size of the decision tree and b is a constant determined by the weak learning hypothesis. Here we consider the case of decision DAGs—decision trees in which a given node can be shared by different branches of the tree, also called branching programs (BP). Node sharing allows a branching program to… CONTINUE READING

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