ConfusionMatrixReport#

class ConfusionMatrixReport[source]#

Calculate the confusion matrix of the model on the given dataset.

Parameters
normalize_displaybool , default: True:

boolean that determines whether to normalize the values of the matrix in the display.

n_samplesint , default: 10_000

number of samples to use for this check.

random_stateint, default: 42

random seed for all check internals.

__init__(normalize_display: bool = True, n_samples: int = 1000000, random_state: int = 42, **kwargs)[source]#
__new__(*args, **kwargs)#

Methods

ConfusionMatrixReport.add_condition(name, ...)

Add new condition function to the check.

ConfusionMatrixReport.add_condition_misclassified_samples_lower_than_condition([...])

Add condition - Misclassified samples lower than threshold.

ConfusionMatrixReport.clean_conditions()

Remove all conditions from this check instance.

ConfusionMatrixReport.conditions_decision(result)

Run conditions on given result.

ConfusionMatrixReport.config([...])

Return check configuration (conditions' configuration not yet supported).

ConfusionMatrixReport.from_config(conf[, ...])

Return check object from a CheckConfig object.

ConfusionMatrixReport.from_json(conf[, ...])

Deserialize check instance from JSON string.

ConfusionMatrixReport.metadata([with_doc_link])

Return check metadata.

ConfusionMatrixReport.name()

Name of class in split camel case.

ConfusionMatrixReport.params([show_defaults])

Return parameters to show when printing the check.

ConfusionMatrixReport.remove_condition(index)

Remove given condition by index.

ConfusionMatrixReport.run(dataset[, model, ...])

Run check.

ConfusionMatrixReport.run_logic(context, ...)

Run check.

ConfusionMatrixReport.to_json([indent, ...])

Serialize check instance to JSON string.

Examples#