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Oracle bounds and exact algorithm for dyadic classification trees

: Blanchard, G.; Schäfer, C.; Rozenholc, Y.

Shawe-Taylor, J.:
Learning theory. 17th Annual Conference on Learning Theory, COLT 2004 : Banff, Canada, July 1 - 4, 2004 ; proceedings
Berlin: Springer, 2004 (Lecture Notes in Artificial Intelligence 3120)
ISBN: 3-540-22282-0
ISSN: 0302-9743
Annual Conference on Learning Theory (COLT) <17, 2004, Banff>
Conference Paper
Fraunhofer FIRST ()

This paper introduces a new method using dyadic decision trees for estimating a classification or a regression function in a multi-class 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.