fairlearn.metrics.true_negative_rate(y_true, y_pred, sample_weight=None, pos_label=None)[source]#

Calculate the true negative rate (also called specificity or selectivity).

Read more in the User Guide.

  • y_true (array-like) – The list of true values

  • y_pred (array-like) – The list of predicted values

  • sample_weight (array-like, optional) – A list of weights to apply to each sample. By default all samples are weighted equally

  • pos_label (scalar, optional) – The value to treat as the ‘positive’ label in the samples. If None (the default) then the largest unique value of the y arrays will be used.


The true negative rate for the data

Return type: