Gadat, Sébastien, Gerchinovitz, Sebastien and Marteau, Clément (2018) Optimal functional supervised classification with separation condition. TSE Working Paper, n. 18-904, Toulouse
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Abstract
We consider the binary supervised classification problem with the Gaussian functional model introduced in [7]. Taking advantage of the Gaussian structure, we design a natural plug-in classifier and derive a family of upper bounds on its worst-case excess risk over Sobolev spaces. These bounds are parametrized by a separation distance quantifying the difficulty of the problem, and are proved to be optimal (up to logarithmic factors) through matching minimax lower bounds. Using the recent works of [9] and [14] we also derive a logarithmic lower bound showing that the popular k-nearest neighbors classifier is far from optimality in this specific functional setting.
Item Type: | Monograph (Working Paper) |
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Language: | English |
Date: | March 2018 |
Place of Publication: | Toulouse |
Subjects: | B- ECONOMIE ET FINANCE |
Divisions: | TSE-R (Toulouse) |
Institution: | Université Toulouse 1 Capitole |
Site: | UT1 |
Date Deposited: | 24 Apr 2018 11:23 |
Last Modified: | 02 Apr 2021 15:57 |
OAI Identifier: | oai:tse-fr.eu:32574 |
URI: | https://publications.ut-capitole.fr/id/eprint/25890 |