ClassImbalance

class ClassImbalance

Check if a dataset is imbalanced by looking at the target variable distribution.

Parameters

n_top_labels: int, default: 5

Number of labels to show in display graph

ignore_nan: bool, default True

Whether to ignore NaN values in the target variable when counting the number of unique values.

__init__(n_top_labels: int = 5, ignore_nan: bool = True, **kwargs)

__new__(*args, **kwargs)

Methods

ClassImbalance.add_condition(name, ...)	Add new condition function to the check.
ClassImbalance.add_condition_class_ratio_less_than([...])	Add condition - ratio between least to most frequent labels.
ClassImbalance.clean_conditions()	Remove all conditions from this check instance.
ClassImbalance.conditions_decision(result)	Run conditions on given result.
ClassImbalance.config([include_version])	Return check configuration (conditions' configuration not yet supported).
ClassImbalance.from_config(conf[, ...])	Return check object from a CheckConfig object.
ClassImbalance.from_json(conf[, version_unmatch])	Deserialize check instance from JSON string.
ClassImbalance.metadata([with_doc_link])	Return check metadata.
ClassImbalance.name()	Name of class in split camel case.
ClassImbalance.params([show_defaults])	Return parameters to show when printing the check.
ClassImbalance.remove_condition(index)	Remove given condition by index.
ClassImbalance.run(dataset[, model, ...])	Run check.
ClassImbalance.run_logic(context, dataset_kind)	Run the check.
ClassImbalance.to_json([indent])	Serialize check instance to JSON string.

Examples

Class Imbalance

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ConflictingLabels.to_json

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ClassImbalance.add_condition