MultiOutputClassificationMetric¶

Mother class for all multi-output classification metrics.

Parameters¶

cm (river.metrics.multioutput.confusion.MultiLabelConfusionMatrix) – defaults to None

This parameter allows sharing the same confusion matrix between multiple metrics. Sharing a confusion matrix reduces the amount of storage and computation time.

bigger_is_better

Indicate if a high value is better than a low one or not.
requires_labels
works_with_weights

Indicate whether the model takes into consideration the effect of sample weights

get

Return the current value of the metric.

is_better_than

revert

Revert the metric.

Parameters

y_true (Dict[Union[str, int], Union[bool, str, int]])
y_pred (Union[Dict[Union[str, int], Union[bool, str, int]], Dict[Union[str, int], Dict[Union[bool, str, int], float]]])
sample_weight – defaults to 1.0

update

Update the metric.

Parameters

y_true (Dict[Union[str, int], Union[bool, str, int]])
y_pred (Union[Dict[Union[str, int], Union[bool, str, int]], Dict[Union[str, int], Dict[Union[bool, str, int], float]]])
sample_weight – defaults to 1.0

works_with

Indicates whether or not a metric can work with a given model.

Parameters