confusion_matrix#
- bayesflow.utils.confusion_matrix(targets: ndarray, estimates: ndarray, labels: Sequence = None, normalize: str = None)[source]#
Compute confusion matrix to evaluate the accuracy of a classification or model comparison setting.
Code inspired by: scikit-learn/scikit-learn
- Parameters:
- targetsnp.ndarray
Ground truth (correct) target values.
- estimatesnp.ndarray
Estimated targets as returned by a classifier.
- labelsSequence, optional
List of labels to index the matrix. This may be used to reorder or select a subset of labels. If None, labels that appear at least once in y_true or y_pred are used in sorted order.
- normalize{‘true’, ‘pred’, ‘all’}, optional
Normalizes confusion matrix over the true (rows), predicted (columns) conditions or all the population. If None, no normalization is applied.
- Returns:
- cmnp.ndarray of shape (num_labels, num_labels)
Confusion matrix. Rows represent true classes, columns represent predicted classes.