metrics | R Documentation |
Returns model metrics from nestedcv models. Extended metrics including
metrics(object, extra = FALSE, innerCV = FALSE, positive = 2)
object |
A 'nestcv.glmnet', 'nestcv.train', 'nestcv.SuperLearner' or 'outercv' object. |
extra |
Logical whether additional performance metrics are gathered for binary classification models: area under precision recall curve (PR.AUC), Cohen's kappa, F1 score, Matthew's correlation coefficient (MCC). |
innerCV |
Whether to calculate metrics for inner CV folds. Only available for 'nestcv.glmnet' and 'nestcv.train' objects. |
positive |
For binary classification, either an integer 1 or 2 for the
level of response factor considered to be 'positive' or 'relevant', or a
character value for that factor. This affects the F1 score. See
|
Area under precision recall curve is estimated by trapezoidal estimation
using MLmetrics::PRAUC()
.
A named numeric vector of performance metrics.
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