High-dimensional variable selection in regression and classification with missing data

Qi Gao; Thomas C. M. Lee

doi:10.1016/j.sigpro.2016.07.014

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High-dimensional variable selection in regression and classification with missing data

Qi Gao Thomas C. M. Lee

Year: 2016 Journal: Signal Processing Vol: 131 Pages: 1-7 Publisher: Elsevier BV

DOI: 10.1016/j.sigpro.2016.07.014

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Keywords:

Missing data Feature selection Lasso (programming language) Data mining Computer science Variable (mathematics) Regression Selection (genetic algorithm) Regression analysis Algorithm Artificial intelligence Machine learning Mathematics Statistics

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Bayesian Methods and Mixture Models

Physical Sciences → Computer Science → Artificial Intelligence

Soil Geostatistics and Mapping

Physical Sciences → Environmental Science → Environmental Engineering

Statistical Methods and Inference

Physical Sciences → Mathematics → Statistics and Probability

High-dimensional variable selection in regression and classification with missing data

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