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Quantile Regression Forests.

Abstract:

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 qu...

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Publication status:
Published

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Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Role:
Author
Journal:
Journal of Machine Learning Research
Volume:
7
Pages:
983-999
Publication date:
2006-01-01
EISSN:
1533-7928
ISSN:
1532-4435
Language:
English
Keywords:
Pubs id:
pubs:97763
UUID:
uuid:36811df5-18b6-45e5-a98b-a4548d3d2107
Local pid:
pubs:97763
Source identifiers:
97763
Deposit date:
2012-12-19

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