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arXiv · 0705.0211

Multilayer Perceptron with Functional Inputs: an Inverse Regression Approach

Louis Ferré·Nathalie Villa
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Abstract

Functional data analysis is a growing research field as more and more practical applications involve functional data. In this paper, we focus on the problem of regression and classification with functional predictors: the model suggested combines an efficient dimension reduction procedure [functional sliced inverse regression, first introduced by Ferré & Yao (Statistics, 37, 2003, 475)], for which we give a regularized version, with the accuracy of a neural network. Some consistency results are given and the method is successfully confronted to real-life data.

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Louis Ferré, Nathalie Villa. 2007-05-02. Multilayer Perceptron with Functional Inputs: an Inverse Regression Approach. https://doi.org/10.1111/j.1467-9469.2006.00496.x

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