ConfusionMatrixDisplay#

class skore.ConfusionMatrixDisplay(*, confusion_matrix, display_labels, report_type)[source]#

Display for confusion matrix.

Parameters:
confusion_matrixpd.DataFrame

Confusion matrix data in long format with columns: “True label”, “Predicted label”, “count”, “normalized_by_true”, “normalized_by_pred”, and “normalized_by_all”. Each row represents one cell of the confusion matrix.

display_labelslist of str

Display labels for plot axes.

report_type{“comparison-cross-validation”, “comparison-estimator”, “cross-validation”, “estimator”}

The type of report.

Attributes:
figure_matplotlib Figure

Figure containing the confusion matrix.

ax_matplotlib Axes

Axes with confusion matrix.

frame(normalize=None)[source]#

Return the confusion matrix as a dataframe.

Parameters:
normalize{‘true’, ‘pred’, ‘all’}, default=None

Normalizes confusion matrix over the true (rows), predicted (columns) conditions or all the population. If None, the confusion matrix will not be normalized.

Returns:
framepandas.DataFrame

The confusion matrix as a dataframe in pivot format with true labels as rows and predicted labels as columns. Values are counts or normalized values depending on the normalize parameter.

help()[source]#

Display available attributes and methods using rich.

plot(*, normalize=None, heatmap_kwargs=None)[source]#

Plot visualization.

Parameters:
normalize{‘true’, ‘pred’, ‘all’}, default=None

Normalizes confusion matrix over the true (rows), predicted (columns) conditions or all the population. If None, the confusion matrix will not be normalized.

heatmap_kwargsdict, default=None

Additional keyword arguments to be passed to seaborn’s sns.heatmap.

Returns:
selfConfusionMatrixDisplay

Configured with the confusion matrix.

set_style(*, policy='override', **kwargs)[source]#

Set the style parameters for the display.

Parameters:
policyLiteral[“override”, “update”], default=”override”

Policy to use when setting the style parameters. If “override”, existing settings are set to the provided values. If “update”, existing settings are not changed; only settings that were previously unset are changed.

**kwargsdict

Style parameters to set. Each parameter name should correspond to a a style attribute passed to the plot method of the display.

Returns:
selfobject

Returns the instance itself.

Raises:
ValueError

If a style parameter is unknown.

static style_plot(plot_func)[source]#

Apply consistent style to skore displays.

This decorator: 1. Applies default style settings 2. Executes plot_func 3. Calls plt.tight_layout() to make sure axis does not overlap 4. Restores the original style settings

Parameters:
plot_funccallable

The plot function to be decorated.

Returns:
callable

The decorated plot function.