SingleDatasetPerformance

class SingleDatasetPerformance

Calculate performance metrics of a given model on a given dataset.

Parameters

scorers: Union[Dict[str, Union[Callable, str]], List[Any]] , default: None

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

n_samplesOptional[int] , default10000

Number of samples to use for the check. If None, all samples will be used.

__init__(scorers: Optional[Union[Dict[str, Union[str, Callable]], List[Any]]] = None, n_samples: Optional[int] = 10000, **kwargs)

__new__(*args, **kwargs)

Methods

SingleDatasetPerformance.add_condition(name, ...)	Add new condition function to the check.
SingleDatasetPerformance.add_condition_greater_than(...)	Add condition - the result is greater than the threshold.
SingleDatasetPerformance.add_condition_less_than(...)	Add condition - the result is less than the threshold.
SingleDatasetPerformance.clean_conditions()	Remove all conditions from this check instance.
SingleDatasetPerformance.compute(context, ...)	Compute the metric result using the ignite metrics compute method and reduce to a scalar.
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.initialize_run(...)	Initialize the metric for the check, and validate task type is relevant.
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.to_json([indent, ...])	Serialize check instance to JSON string.
SingleDatasetPerformance.update(context, ...)	Update the metrics by passing the batch to ignite metric update method.

Examples

Single Dataset Performance

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SimpleModelComparison.update

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SingleDatasetPerformance.add_condition