Description Usage Arguments Value Meta Information Note References See Also Examples

Computes the area under the Receiver Operator Characteristic (ROC) curve. The AUC can be interpreted as the probability that a randomly chosen positive observation has a higher predicted probability than a randomly chosen negative observation.

1 |

`truth` |
:: |

`prob` |
:: |

`positive` |
:: |

`na_value` |
:: |

`...` |
:: |

Performance value as `numeric(1)`

.

Type:

`"binary"`

Range:

*[0, 1]*Minimize:

`FALSE`

Required prediction:

`prob`

This measure is undefined if the true values are either all positive or all negative.

youden_1950

Other Binary Classification Measures: `dor`

,
`fbeta`

, `fdr`

,
`fnr`

, `fn`

, `fomr`

,
`fpr`

, `fp`

, `mcc`

,
`npv`

, `ppv`

, `tnr`

,
`tn`

, `tpr`

, `tp`

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