10-601 Ensembles 1

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This a lecture used in the Syllabus for Machine Learning 10-601

Slides

Readings

Summary

You should know how to implement these ensemble methods, and what their relative advantages and disadvantages are:

  • Bagging
  • Boosting
  • Stacking
  • Multilevel Stacking
  • The "bucket of models" classifier