balancedFolds: Function producing stratified/ balanced folds for cross...

In c060: Extended Inference for Lasso and Elastic-Net Regularized Cox and Generalized Linear Models

Function producing stratified/ balanced folds for cross validation

Description

Get balanced folds for cross validation, which are used for tuning penalization parameters

Usage

balancedFolds(class.column.factor, cross.outer) 

Arguments

class.column.factor	class labels of length n
cross.outer	number of folds

Value

permutated.cut	vector of length n, indicating the fold belongs to
model	model list alpha - optimal alpha lambda - optimal lambda nfolds - cross-validation's folds cvreg - cv.glmnet object for optimal alpha fit - glmnet object for optimal alpha and optimal lambda

Author(s)

Natalia Becker natalia.becker at dkfz.de

References

Sill M., Hielscher T., Becker N. and Zucknick M. (2014), c060: Extended Inference with Lasso and Elastic-Net Regularized Cox and Generalized Linear Models, Journal of Statistical Software, Volume 62(5), pages 1–22. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.18637/jss.v062.i05")}

See Also

EPSGO

c060 documentation built on March 31, 2023, 5:15 p.m.