Corpus ID: 165022

Mondrian Forests for Large-Scale Regression when Uncertainty Matters

@article{Lakshminarayanan2016MondrianFF,
  title={Mondrian Forests for Large-Scale Regression when Uncertainty Matters},
  author={Balaji Lakshminarayanan and D. M. Roy and Y. Teh},
  journal={ArXiv},
  year={2016},
  volume={abs/1506.03805}
}
  • Balaji Lakshminarayanan, D. M. Roy, Y. Teh
  • Published 2016
  • Mathematics, Computer Science
  • ArXiv
  • Many real-world regression problems demand a measure of the uncertainty associated with each prediction. Standard decision forests deliver efficient state-of-the-art predictive performance, but high-quality uncertainty estimates are lacking. Gaussian processes (GPs) deliver uncertainty estimates, but scaling GPs to large-scale data sets comes at the cost of approximating the uncertainty estimates. We extend Mondrian forests, first proposed by Lakshminarayanan et al. (2014) for classification… CONTINUE READING

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