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

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

Natalia Becker natalia.becker at dkfz.de

See also

EPSGO

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. https://www.jstatsoft.org/v062/i05/