RegressionErrorDistribution

class RegressionErrorDistribution

Check regression error distribution.

The check shows the distribution of the regression error, and enables to set conditions on the distribution kurtosis. Kurtosis is a measure of the shape of the distribution, helping us understand if the distribution is significantly “wider” from the normal distribution, which may imply a certain cause of error deforming the normal shape.

Parameters

n_top_samplesint , default: 3

amount of samples to show which have the largest under / over estimation errors.

n_binsint , default: 40

number of bins to use for the histogram.

__init__(n_top_samples: int = 3, n_bins: int = 40, **kwargs)

__new__(*args, **kwargs)

Methods

RegressionErrorDistribution.add_condition(...)	Add new condition function to the check.
RegressionErrorDistribution.add_condition_kurtosis_greater_than([...])	Add condition - require min kurtosis value to be greater than the threshold.
RegressionErrorDistribution.clean_conditions()	Remove all conditions from this check instance.
RegressionErrorDistribution.conditions_decision(result)	Run conditions on given result.
RegressionErrorDistribution.config()	Return check configuration (conditions' configuration not yet supported).
RegressionErrorDistribution.from_config(conf)	Return check object from a CheckConfig object.
RegressionErrorDistribution.metadata([...])	Return check metadata.
RegressionErrorDistribution.name()	Name of class in split camel case.
RegressionErrorDistribution.params([...])	Return parameters to show when printing the check.
RegressionErrorDistribution.remove_condition(index)	Remove given condition by index.
RegressionErrorDistribution.run(dataset[, ...])	Run check.
RegressionErrorDistribution.run_logic(...)	Run check.

Examples

Regression Error Distribution

previous

PerformanceReport.run_logic

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RegressionErrorDistribution.add_condition