dataeval.metrics.bias.DiversityOutput¶

class dataeval.metrics.bias.DiversityOutput¶

Output class for diversity() bias metric.

diversity_index¶

Diversity index for classes and factors

Type:¶

NDArray[np.double]

classwise¶

Classwise diversity index [n_class x n_factor]

Type:¶

NDArray[np.double]

factor_names¶

Names of each metadata factor

Type:¶

Sequence[str]

class_names¶

Class labels for each value in the dataset

Type:¶

Sequence[str]

data()¶

The output data as a dictionary.

Return type:¶

dict[str, Any]

meta()¶

Metadata about the execution of the function or method for the Output class.

Return type:¶

ExecutionMetadata

plot(row_labels=None, col_labels=None, plot_classwise=False)¶

Plot a heatmap of diversity information.

Parameters:¶

row_labels : ArrayLike or None, default None¶

List/Array containing the labels for rows in the histogram

col_labels : ArrayLike or None, default None¶

List/Array containing the labels for columns in the histogram

plot_classwise : bool, default False¶

Whether to plot per-class balance instead of global balance

Return type:¶

matplotlib.figure.Figure

Notes

This method requires matplotlib to be installed.