Handling missing values in support vector machine classifiers

DOI10.1016/j.neunet.2005.06.025zbMath1077.68777OpenAlexW1992329416WikidataQ47371482 ScholiaQ47371482MaRDI QIDQ2568021

Bart De Moor, Johan A. K. Suykens, J. De Brabanter, Kristiaan Pelckmans

Publication date: 7 October 2005

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2005.06.025

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (13)

Mean field variational Bayesian inference for support vector machine classification ⋮ A new robust model of one-class classification by interval-valued training data using the triangular kernel ⋮ Data filtering for cluster analysis by \(\ell _0\)-norm regularization ⋮ Evidence integration credal classification algorithm versus missing data distributions ⋮ Kernel machines with missing covariates ⋮ Discriminative training of feed-forward and recurrent sum-product networks by extended Baum-Welch ⋮ Kernel machines with missing responses ⋮ Solution path clustering with adaptive concave penalty ⋮ A kernel PLS based classification method with missing data handling ⋮ Learning with tensors: a framework based on convex optimization and spectral regularization ⋮ Pointed subspace approach to incomplete data ⋮ Handling missing values in support vector machine classifiers ⋮ Techniques for dealing with incomplete data: a tutorial and survey

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• Inference and missing data
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• Bayesian Framework for Least-Squares Support Vector Machine Classifiers, Gaussian Processes, and Kernel Fisher Discriminant Analysis
• Advanced Lectures on Machine Learning
• The elements of statistical learning. Data mining, inference, and prediction

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