A nonlinear aggregation type classifier

Alejandro Cholaquidis; Ricardo Fraiman; Juan Kalemkerian; Pamela Llop

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arXiv · 1509.01604

A nonlinear aggregation type classifier

Alejandro Cholaquidis·Ricardo Fraiman·Juan Kalemkerian·Pamela Llop

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Abstract

We introduce a nonlinear aggregation type classifier for functional data defined on a separable and complete metric space. The new rule is built up from a collection of $M$ arbitrary training classifiers. If the classifiers are consistent, then so is the aggregation rule. Moreover, asymptotically the aggregation rule behaves as well as the best of the $M$ classifiers. The results of a small simulation are reported both, for high dimensional and functional data, and a real data example is analyzed.

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Alejandro Cholaquidis, Ricardo Fraiman, Juan Kalemkerian, Pamela Llop. 2015-09-04. A nonlinear aggregation type classifier. https://arxiv.org/abs/1509.01604

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