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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 )

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.

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` . |

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Licensed under the Creative Commons Attribution License 3.0.

Code samples licensed under the Apache 2.0 License.

https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/math/confusion_matrix