Multilayer Perceptron with Functional Inputs: an Inverse Regression Approach

DOI10.1111/j.1467-9469.2006.00496.xzbMath1164.62339arXiv0705.0211OpenAlexW2019697858MaRDI QIDQ5430622

Nathalie Villa, Louis Ferré

Publication date: 16 December 2007

Published in: Scandinavian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0705.0211

zbMATH Keywords

dimension reductionfunctional data analysisfunctional sliced inverse regression

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20) Generalized linear models (logistic models) (62J12) Nonparametric inference (62G99)

Related Items (12)

Functional \(k\)-means inverse regression ⋮ Supervised Classification for a Family of Gaussian Functional Models ⋮ Functional data analysis in shape analysis ⋮ Fast \(DD\)-classification of functional data ⋮ Nonstationary Gaussian Process Discriminant Analysis With Variable Selection for High-Dimensional Functional Data ⋮ Functional linear regression after spline transformation ⋮ Multiclass functional discriminant analysis and its application to gesture recognition ⋮ Interpretable sparse SIR for functional data ⋮ A Bayesian Hierarchical Model for Classification with Selection of Functional Predictors ⋮ No effect tests in regression on functional variable and some applications to spectrometric studies ⋮ Functional classification of ornamental stone using machine learning techniques ⋮ Kernel sliced inverse regression: regularization and consistency

Uses Software

• fda (R)

Cites Work

• Curves discrimination: a nonparametric functional approach
• Functional data analysis
• Network approximation of input-output maps and functionals
• Functional multi-layer perceptron: A nonlinear tool for functional data analysis
• Functional linear model
• Asymptotics for kernel estimate of sliced inverse regression
• Un modèle semi-paramétrique pour variables aléatoires hilbertiennes
• Functional Classification in Hilbert Spaces
• Sliced Inverse Regression for Dimension Reduction
• Flexible Discriminant Analysis by Optimal Scoring
• Clustering for Sparsely Sampled Functional Data
• An Adaptive Estimation of Dimension Reduction Space
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