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Predict with training quantiles by default #668

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merged 2 commits into from May 13, 2020
Merged

Predict with training quantiles by default #668

merged 2 commits into from May 13, 2020

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erikcs
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@erikcs erikcs commented May 13, 2020

Closes #667.

X = matrix(rnorm(100*10), 100, 10)
Y = rnorm(100)
qrf = quantile_forest(X, Y, quantiles=c(0.2, 0.8))
p = predict(qrf, X)

dim(p)
#[1] 100   2

jtibshirani
jtibshirani approved these changes May 13, 2020
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Thanks for the fast turnaround on this bug!

r-package/grf/R/quantile_forest.R Outdated Show resolved Hide resolved
@erikcs erikcs merged commit 929afc7 into grf-labs:master May 13, 2020
@erikcs erikcs deleted the use-training-quantiles branch May 13, 2020 04:59
erikcs added a commit to erikcs/grf that referenced this pull request Jun 12, 2020
@erikcs
Merge branch 'master' into xptr-revised
1e305e7 
* master:
  Correct the generated documentation for `best_linear_projection` (grf-labs#689)
  Fix the default `prediction.type` in survival predict (grf-labs#686)
  Add optional Nelson-Aalen estimates of the survival function (grf-labs#685)
  Clarify the survival forest prediction documentation (grf-labs#681)
  Prepare the 1.2.0 release (grf-labs#679)
  Add survival/quantile/local linear timings to benchmark script (grf-labs#680)
  Fix punctuation. (grf-labs#677)
  Update references in README (grf-labs#676)
  README: add the grant number to ONR (grf-labs#675)
  Add an acknowledgements section to README (grf-labs#674)
  Remove passing explicit default options to `findInterval()` (grf-labs#673)
  Add option to predict at chosen failure times (grf-labs#672)
  Simplify some R build options in Travis (grf-labs#670)
  Make consistent use of logical operators in R bindings (grf-labs#669)
  Predict with training quantiles by default (grf-labs#668)
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Quantile forest prediction should use training quantiles by default
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@erikcs @jtibshirani