Can Hyperparameter Tuning Improve the Performance of a Super Learner?: A Case Study.

Journal: Epidemiology (Cambridge, Mass.)
Published Date: Jul 1, 2019

Abstract

BACKGROUND: Super learning is an ensemble machine learning approach used increasingly as an alternative to classical prediction techniques. When implementing super learning, however, not tuning the hyperparameters of the algorithms in it may adversely affect the performance of the super learner.

Authors

  • Jenna Wong
    Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Canada.
  • Travis Manderson
    School of Computer Science, McGill University, Montreal, Canada.
  • Michal Abrahamowicz
    Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Canada.
  • David L Buckeridge
    Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Québec, Canada.
  • Robyn Tamblyn
    Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Canada.

Keywords

External Resources

Popular Topics
Recent Journals