`sklearn.metrics`.ConfusionMatrixDisplay¶

class sklearn.metrics.ConfusionMatrixDisplay(confusion_matrix, *, display_labels=None)[source]¶

Confusion Matrix visualization.

It is recommend to use plot_confusion_matrix to create a ConfusionMatrixDisplay. All parameters are stored as attributes.

Read more in the User Guide.

Parameters

confusion_matrixndarray of shape (n_classes, n_classes): Confusion matrix.
display_labelsndarray of shape (n_classes,), default=None: Display labels for plot. If None, display labels are set from 0 to n_classes - 1.

Attributes

im_matplotlib AxesImage: Image representing the confusion matrix.
text_ndarray of shape (n_classes, n_classes), dtype=matplotlib Text, or None: Array of matplotlib axes. None if include_values is false.
ax_matplotlib Axes: Axes with confusion matrix.
figure_matplotlib Figure: Figure containing the confusion matrix.

Methods

plot(*[, include_values, cmap, …])

Plot visualization.

__init__(confusion_matrix, *, display_labels=None)[source]¶: Initialize self. See help(type(self)) for accurate signature.

plot(*, include_values=True, cmap='viridis', xticks_rotation='horizontal', values_format=None, ax=None)[source]¶

Plot visualization.

Parameters

include_valuesbool, default=True: Includes values in confusion matrix.
cmapstr or matplotlib Colormap, default=’viridis’: Colormap recognized by matplotlib.
xticks_rotation{‘vertical’, ‘horizontal’} or float, default=’horizontal’: Rotation of xtick labels.
values_formatstr, default=None: Format specification for values in confusion matrix. If None, the format specification is ‘d’ or ‘.2g’ whichever is shorter.
axmatplotlib axes, default=None: Axes object to plot on. If None, a new figure and axes is created.

Returns

Examples using `sklearn.metrics.ConfusionMatrixDisplay`¶