A kernel PLS based classification method with missing data handling

DOI10.1007/S00362-015-0694-YzbMath1394.62087OpenAlexW600012497MaRDI QIDQ513700

Yury Tsoy, Thuy Tuong Nguyen

Publication date: 7 March 2017

Published in: Statistical Papers (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00362-015-0694-y

zbMATH Keywords

classificationdiscriminant analysismissing dataPLSkernel partial least squares

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (1)

CLT for integrated square error of density estimators with censoring indicators missing at random

Cites Work

• Comparison of PLS algorithms when number of objects is much larger than number of variables
• Benchmarking least squares support vector machine classifiers
• Handling missing values in support vector machine classifiers
• Improvements on Cross-Validation: The .632+ Bootstrap Method
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