innercv_summary: Summarise performance on inner CV test folds
In nestedcv: Nested Cross-Validation with 'glmnet' and 'caret'

innercv_summary

R Documentation

Summarise performance on inner CV test folds

Description

Calculates performance metrics on inner CV held-out test folds: confusion matrix, accuracy and balanced accuracy for classification; ROC AUC for binary classification; RMSE, R^2 and mean absolute error (MAE) for regression.

Usage

innercv_summary(x)

Arguments

`x`	a `nestcv.glmnet` or `nestcv.train` object

Value

Returns performance metrics from outer training folds, see predSummary.

Examples

data(iris)
x <- iris[, 1:4]
y <- iris[, 5]

fit <- nestcv.glmnet(y, x,
                     family = "multinomial",
                     alpha = 1,
                     n_outer_folds = 3)
summary(fit)
innercv_summary(fit)

nestedcv documentation built on Oct. 26, 2023, 5:08 p.m.