SingleDatasetPerformance#

class SingleDatasetPerformance[source]#

Summarize given model performance on the train and test datasets based on selected scorers.

Parameters
scorers: Union[Mapping[str, Union[str, Callable]], List[str]], default: None

Scorers to override the default scorers, find more about the supported formats at https://docs.deepchecks.com/stable/user-guide/general/metrics_guide.html

n_samplesint , default: 1_000_000

number of samples to use for this check.

random_stateint, default: 42

random seed for all check internals.

__init__(scorers: Optional[Union[Mapping[str, Union[str, Callable]], List[str]]] = None, n_samples: int = 1000000, random_state: int = 42, **kwargs)[source]#
__new__(*args, **kwargs)#

Methods

SingleDatasetPerformance.add_condition(name, ...)

Add new condition function to the check.

SingleDatasetPerformance.add_condition_greater_than(...)

Add condition - the selected metrics scores are greater than the threshold.

SingleDatasetPerformance.clean_conditions()

Remove all conditions from this check instance.

SingleDatasetPerformance.conditions_decision(result)

Run conditions on given result.

SingleDatasetPerformance.config([...])

Return check configuration.

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

Return check object from a CheckConfig object.

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

Deserialize check instance from JSON string.

SingleDatasetPerformance.greater_is_better()

Return True if the check reduce_output is better when it is greater.

SingleDatasetPerformance.metadata([...])

Return check metadata.

SingleDatasetPerformance.name()

Name of class in split camel case.

SingleDatasetPerformance.params([show_defaults])

Return parameters to show when printing the check.

SingleDatasetPerformance.reduce_output(...)

Return the values of the metrics for the dataset provided in a {metric: value} format.

SingleDatasetPerformance.remove_condition(index)

Remove given condition by index.

SingleDatasetPerformance.run(dataset[, ...])

Run check.

SingleDatasetPerformance.run_logic(context, ...)

Run check.

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

Serialize check instance to JSON string.

Examples#