Random Forests

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Authors: Leo Breiman
Year: 2001
Journal: Machine Learning
DOI: 10.1023/A:1010933404324
Publisher: https://link.springer.com/article/10.1023/A:1010933404324

Keywords: random forest, ensemble

Abstract

Random forests are a combination of tree predictors such that each tree depends on the values of a random vector sampled independently.

Cite this paper

bibtex

@misc{randomforest2001,
  title  = {Random Forests},
  author = {Leo Breiman},
  year   = {2001},
  journal = {Machine Learning},
  doi    = {10.1023/A:1010933404324},
  url    = {https://doi.org/10.1023/A:1010933404324},
}

Source files

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[paper.bib](https://raw.githubusercontent.com/badhope/ScholarLib/main/papers/computer-science/Machine-Learning/Foundations/2019-and-earlier/Machine Learning/empirical/ensemble/random-forest/paper.bib)