Functional-bandwidth kernel for support vector machine with functional data: an alternating optimization algorithm

DOI10.1016/j.ejor.2018.11.024zbMath1430.90450OpenAlexW2901418248WikidataQ128879958 ScholiaQ128879958MaRDI QIDQ1711465

Emilio Carrizosa, Belén Martín-Barragán, Rafael Blanquero, Asunción Jiménez-Cordero

Publication date: 18 January 2019

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://www.pure.ed.ac.uk/ws/files/78237973/BlanqueroEtalEJOR2018FunctionalBandwidthKernel.pdf

zbMATH Keywords

data miningSVMparameter tuningfunctional data classificationfunctional bandwidth

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Quadratic programming (90C20) Pattern recognition, speech recognition (68T10)

Related Items (9)

Mathematical optimization in classification and regression trees ⋮ Selection of time instants and intervals with support vector regression for multivariate functional data ⋮ Classification of multivariate functional data on different domains with partial least squares approaches ⋮ Robust low-rank multiple kernel learning with compound regularization ⋮ Variable selection in classification for multivariate functional data ⋮ A kernel-free double well potential support vector machine with applications ⋮ A dual reformulation and solution framework for regularized convex clustering problems ⋮ A novel embedded min-max approach for feature selection in nonlinear support vector machine classification ⋮ Unsupervised quadratic surface support vector machine with application to credit risk assessment

Uses Software

• fda (R)
• fda.usc

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