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A Simple Boosting Algorithm Using Multi-Way Branching Decision Trees

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Abstract

We improve the analysis of the decision tree boosting algorithm proposed by Mansour and McAllester. For binary classification problems, the algorithm of Mansour and McAllester constructs a multi-way branching decision tree using a set of multi-class hypotheses. Mansour and McAllester proved that it works under certain conditions. We give a rigorous analysis of the algorithm and simplify the conditions. From this simplification, we can provide a simpler algorithm, for which no prior knowledge on the quality of weak hypotheses is necessary.

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  1. Department of Mathematical and Computing Sciences, Tokyo Institute of Technology, Ookayama 2-12-1, Meguro-ku, Tokyo 152-8552, Japan

    Kohei Hatano

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  1. Kohei Hatano
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Correspondence to Kohei Hatano.

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Hatano, K. A Simple Boosting Algorithm Using Multi-Way Branching Decision Trees. Theory Comput Systems 37, 503–518 (2004). https://doi.org/10.1007/s00224-003-1064-z

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  • DOI: https://doi.org/10.1007/s00224-003-1064-z

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