Corpus ID: 28528

Quantile Regression Forests

@article{Meinshausen2006QuantileRF,
  title={Quantile Regression Forests},
  author={N. Meinshausen},
  journal={J. Mach. Learn. Res.},
  year={2006},
  volume={7},
  pages={983-999}
}
  • N. Meinshausen
  • Published 2006
  • Mathematics, Computer Science
  • J. Mach. Learn. Res.
  • Random forests were introduced as a machine learning tool in Breiman (2001) and have since proven to be very popular and powerful for high-dimensional regression and classification. For regression, random forests give an accurate approximation of the conditional mean of a response variable. It is shown here that random forests provide information about the full conditional distribution of the response variable, not only about the conditional mean. Conditional quantiles can be inferred with… CONTINUE READING
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