View source: R/brier_table.CV.SuperLearner.R
brier_table.CV.SuperLearner | R Documentation |
Calculates cross-validated Brier score for each learner in the CV.SuperLearner. Also calculates standard-error, confidence interval and p-value.
## S3 method for class 'CV.SuperLearner'
brier_table(
x,
y = x$Y,
sort = TRUE,
null_hypothesis = NULL,
two_tailed = FALSE,
lower.tail = TRUE,
...
)
x |
CV.SuperLearner object |
y |
Outcome vector, if not already added to CV.SL object. |
sort |
Sort table by order of score. |
null_hypothesis |
Not implemented yet |
two_tailed |
Not implemented yet |
lower.tail |
Not implemented yet |
... |
Any additional unused arguments, due to the prauc_table generic. |
Dataframe table with Brier score and std dev.
library(SuperLearner)
library(ck37r)
data(Boston, package = "MASS")
set.seed(1)
y = as.numeric(Boston$medv > 23)
cvsl = CV.SuperLearner(Y = y,
X = subset(Boston, select = -medv),
family = binomial(),
cvControl = list(V = 2, stratifyCV = TRUE),
SL.library = c("SL.mean", "SL.glm"))
brier_table(cvsl, y = y)
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