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Subfields and ConceptsEdit

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Lecture NotesEdit

Books and Book ChaptersEdit

  • Zhou, Z. H. (2015). "Ensemble Learning". Encyclopedia of biometrics. Springer.
  • Zhou, Z. H. (2012). Ensemble methods: foundations and algorithms. CRC press.
  • Alpaydin, E. (2010). "Chapter 17: Combining Multiple Learners". Introduction to machine learning. MIT Press.
  • Russell, S. J., & Norvig, P. (2010). "Section 18.10: Ensemble Learning". Artificial Intelligence: A Modern Approach. Prentice Hall.
  • Bishop, C. M. (2006). "Chapter 9: Mixture Models and EM". Pattern Recognition and Machine Learning. Springer.
  • Bishop, C. M. (2006). "Chapter 14: Combining Models". Pattern Recognition and Machine Learning. Springer.
  • Kuncheva, L. I. (2004). Combining pattern classifiers: methods and algorithms. John Wiley & Sons.
  • Dietterich, T. G. (2002). "Ensemble Learning". The handbook of brain theory and neural networks. MIT Press.

Scholarly ArticlesEdit

  • Dzeroski, S., & Zenko, B. (2004). Is combining classifiers with stacking better than selecting the best one?. Machine learning, 54(3), 255-273.

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