innercv_summary {nestedcv}

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.

See Also

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)