View source: R/enr functions.R
en_kfold_accuracy_tied_grid | R Documentation |
This function breaks ties if model performance for grid search enr models is tied (DOCUMENTATION COMING)
en_kfold_accuracy_tied_grid(
tied_alphas,
tied_lambdas,
tied_cutoffs,
ddata,
response_var,
iter = 100,
k = 10,
favor_parsimony = TRUE,
eq_wt = FALSE,
seed = 522,
type_meas = "deviance",
selection_type = "modal"
)
tied_alphas |
a vector of the alphas that are tied |
tied_cutoffs |
a vector of the cutoffs that are tied |
ddata |
data frame containing the data to be modeled |
response_var |
string identifying the name of the outcome variable |
iter |
the number of iterations to use |
k |
the number of folds to use |
favor_parsimony |
boolean indicating if a simpler model should be favored |
eq_wt |
boolean indicating whether the 0/1 classes should be balanced with weights. you may want to use this if there is a bad class imbalance |
seed |
the seed value for allowing results to be reproduced |
type_meas |
the 'type measure' which is passed to cv.glmnet that governs its training penalty when tuning lambda. this should match arguments expected in cv.glmnet |
en_kfold_accuracy_tied_grid()
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.