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) – ground truth class label for each sample

  • y_pred (ndarray) – predicted class label for each sample

  • n_labels (int) – number of labels

  • sample_weight (ndarray | None) – 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])