summary method for the CV.SuperLearner function
# S3 method for CV.SuperLearner
summary(object, obsWeights = NULL, ...)# S3 method for summary.CV.SuperLearner
print(x, digits, ...)
summary.CV.SuperLearner returns a list with components
The function call from CV.SuperLearner
Describes the loss function used. Currently either least squares of negative log Likelihood.
Number of folds
Risk estimate for the super learner
Risk estimate for the discrete super learner (the cross-validation selector)
A matrix with the risk estimates for each algorithm in the library
A table with the mean risk estimate and standard deviation across the folds for the super learner and all algorithms in the library
An object of class "CV.SuperLearner", the result of a call to CV.SuperLearner.
An object of class "summary.CV.SuperLearner", the result of a call to summary.CV.SuperLearner.
Optional vector for observation weights.
The number of significant digits to use when printing.
additional arguments ...
Eric C Polley eric.polley@nih.gov
Summary method for CV.SuperLearner. Calculates the V-fold cross-validated estimate of either the mean squared error or the -2*log(L) depending on the loss function used.
CV.SuperLearner