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COLT
2004
Springer

Oracle Bounds and Exact Algorithm for Dyadic Classification Trees

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Oracle Bounds and Exact Algorithm for Dyadic Classification Trees
This paper introduces a new method using dyadic decision trees for estimating a classification or a regression function in a multiclass classification problem. The estimator is based on model selection by penalized empirical loss minimization. Our work consists in two complementary parts: first, a theoretical analysis of the method leads to deriving oracle-type inequalities for three different possible loss functions. Secondly, we present an algorithm able to compute the estimator in an exact way. 1 General setup
Gilles Blanchard, Christin Schäfer, Yves Roze
Added 20 Aug 2010
Updated 20 Aug 2010
Type Conference
Year 2004
Where COLT
Authors Gilles Blanchard, Christin Schäfer, Yves Rozenholc
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