holisticai.bias.metrics.confusion_matrix

holisticai.bias.metrics.confusion_matrix(y_pred, y_true, classes=None, normalize=None)

Confusion Matrix

This function computes the confusion matrix. The i, jth entry is the number of elements with predicted class i and true class j.

Parameters

y_predarray-like

Prediction vector (categorical)

y_truearray-like

Target vector (categorical)

classeslist, optional

The unique output classes in order

normalizestr, optional

According to which of pred or class we normalize: None, ‘pred’ or ‘class’

Returns

numpy ndarray

Confusion Matrix : shape (num_classes, num_classes)

Examples

>>> import numpy as np
>>> from holisticai.bias.metrics import confusion_matrix
>>> y_pred = np.array([0, 1, 2, 0, 1, 2, 0, 1, 2, 0])
>>> y_true = np.array([0, 1, 1, 0, 1, 0, 2, 1, 2, 1])
>>> confusion_matrix(y_pred, y_true, classes=[2, 1, 0])
    2    1    0
2  1.0  1.0  1.0
1  0.0  3.0  0.0
0  1.0  1.0  2.0