IMAL 13325
INSTITUTO DE MATEMATICA APLICADA DEL LITORAL "DRA. ELEONOR HARBOURE"
Unidad Ejecutora - UE
artículos
Título:
An nonlinear aggregation type classifier
Autor/es:
CHOLAQUIDIS, ALEJANDRO; LLOP, PAMELA; KALEMKERIAN, JUAN; FRAIMAN, RICARDO
Revista:
JOURNAL OF MULTIVARIATE ANALYSIS
Editorial:
ELSEVIER INC
Referencias:
Lugar: Amsterdam ; Año: 2016 vol. 146 p. 269 - 281
ISSN:
0047-259X
Resumen:
We introduce a nonlinear aggregation type classifier for functional data 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.
