en_kfold_accuracy_tied: en_kfold_accuracy_tied function

In clmacleod/highlandr: Random Useful Functions

en_kfold_accuracy_tied function

Description

This function breaks ties if model performance for enr models is tied (DOCUMENTATION COMING)

Usage

en_kfold_accuracy_tied(
  tied_alphas,
  tied_cutoffs,
  ddata,
  response_var,
  iter = 10,
  k = 10,
  favor_parsimony = TRUE,
  eq_wt = FALSE,
  seed = 123,
  type_meas = "deviance"
)

Arguments

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

Examples

en_kfold_accuracy_tied()

clmacleod/highlandr documentation built on April 17, 2025, 3:30 a.m.