train_roc: Build ROC curve from outer CV training folds

In nestedcv: Nested Cross-Validation with 'glmnet' and 'caret'

Build ROC curve from outer CV training folds

Description

Build ROC (receiver operating characteristic) curve from outer training folds. Object can be plotted using plot() or passed to functions pROC::auc() etc.

Usage

train_roc(x, direction = "<", ...)

Arguments

x	a nestcv.glmnet, nestcv.train or outercv object
direction	Set ROC directionality pROC::roc
...	Other arguments passed to pROC::roc

Details

Note: the argument outer_train_predict must be set to TRUE in the original call to either nestcv.glmnet, nestcv.train or outercv.

Value

"roc" object, see pROC::roc

nestedcv documentation built on April 4, 2025, 2:21 a.m.