kwcoco.metrics.functional module¶
- kwcoco.metrics.functional.fast_confusion_matrix(y_true, y_pred, n_labels, sample_weight=None)[source]¶
faster version of sklearn confusion matrix that avoids the expensive checks and label rectification
- Parameters
y_true (ndarray[Any, Int]) – ground truth class label for each sample
y_pred (ndarray[Any, Int]) – predicted class label for each sample
n_labels (int) – number of labels
sample_weight (ndarray) – weight of each sample Extended typing
ndarray[Any, Int | Float]
- Returns
matrix where rows represent real and cols represent pred and the value at each cell is the total amount of weight Extended typing
ndarray[Shape['*, *'], Int64 | Float64]
- Return type
ndarray
Example
>>> y_true = np.array([0, 0, 0, 0, 1, 1, 1, 0, 0, 1]) >>> y_pred = np.array([0, 0, 0, 0, 0, 0, 0, 1, 1, 1]) >>> fast_confusion_matrix(y_true, y_pred, 2) array([[4, 2], [3, 1]]) >>> fast_confusion_matrix(y_true, y_pred, 2).ravel() array([4, 2, 3, 1])