Boosting for Functional Data

Details Boosting for Functional Data Boosting for Functional Data

2006-05-30

arxiv.org/abs/math/0605751v1

Proceedings of the 17th International Conference on Computational Statistics, 2006, pp. 1121-1128

Mathematics

Statistics Theory

Scientific paper

We deal with the task of supervised learning if the data is of functional type. The crucial point is the choice of the appropriate fitting method (learner). Boosting is a stepwise technique that combines learners in such a way that the composite learner outperforms the single learner. This can be done by either reweighting the examples or with the help of a gradient descent technique. In this paper, we explain how to extend Boosting methods to problems that involve functional data.

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