tf.math.bincount

Computes the confusion matrix from predictions and labels.

tf.math.confusion_matrix(
    labels, predictions, num_classes=None, weights=None, dtype=tf.dtypes.int32,
    name=None
)

Used in the notebooks

Used in the tutorials
Simple audio recognition: Recognizing keywords How to solve a problem on Kaggle with TF-Hub

The matrix columns represent the prediction labels and the rows represent the real labels. The confusion matrix is always a 2-D array of shape [n, n], where n is the number of valid labels for a given classification task. Both prediction and labels must be 1-D arrays of the same shape in order for this function to work.

If num_classes is None, then num_classes will be set to one plus the maximum value in either predictions or labels. Class labels are expected to start at 0. For example, if num_classes is 3, then the possible labels would be [0, 1, 2].

If weights is not None, then each prediction contributes its corresponding weight to the total value of the confusion matrix cell.

For example:

  tf.math.confusion_matrix([1, 2, 4], [2, 2, 4]) ==>
      [[0 0 0 0 0]
       [0 0 1 0 0]
       [0 0 1 0 0]
       [0 0 0 0 0]
       [0 0 0 0 1]]

Note that the possible labels are assumed to be [0, 1, 2, 3, 4], resulting in a 5x5 confusion matrix.

Args
`labels`	1-D `Tensor` of real labels for the classification task.
`predictions`	1-D `Tensor` of predictions for a given classification.
`num_classes`	The possible number of labels the classification task can have. If this value is not provided, it will be calculated using both predictions and labels array.
`weights`	An optional `Tensor` whose shape matches `predictions`.
`dtype`	Data type of the confusion matrix.
`name`	Scope name.

Returns
A `Tensor` of type `dtype` with shape `[n, n]` representing the confusion matrix, where `n` is the number of possible labels in the classification task.

Raises
`ValueError`	If both predictions and labels are not 1-D vectors and have mismatched shapes, or if `weights` is not `None` and its shape doesn't match `predictions`.

TensorFlow

tf.math / bincount

Used in the notebooks

For example:

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TensorFlow

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tf.math / bincount

Used in the notebooks

For example:

Args

Returns

Raises