Calculates the mean of the per-class accuracies.

tf.metrics.mean_per_class_accuracy( labels, predictions, num_classes, weights=None, metrics_collections=None, updates_collections=None, name=None )

Calculates the accuracy for each class, then takes the mean of that.

For estimation of the metric over a stream of data, the function creates an `update_op`

operation that updates the accuracy of each class and returns them.

If `weights`

is `None`

, weights default to 1. Use weights of 0 to mask values.

Args | ||
---|---|---|

`labels` | A `Tensor` of ground truth labels with shape [batch size] and of type `int32` or `int64` . The tensor will be flattened if its rank > 1. | |

`predictions` | A `Tensor` of prediction results for semantic labels, whose shape is [batch size] and type `int32` or `int64` . The tensor will be flattened if its rank > 1. | |

`num_classes` | The possible number of labels the prediction task can have. This value must be provided, since two variables with shape = [num_classes] will be allocated. | |

`weights` | Optional `Tensor` whose rank is either 0, or the same rank as `labels` , and must be broadcastable to `labels` (i.e., all dimensions must be either `1` , or the same as the corresponding `labels` dimension). | |

`metrics_collections` | An optional list of collections that `mean_per_class_accuracy' should be added to. </td> </tr><tr> <td>` updates_collections`</td> <td> An optional list of collections` update_op`should be added to. </td> </tr><tr> <td>` name` | An optional variable_scope name. |

Returns | |
---|---|

`mean_accuracy` | A `Tensor` representing the mean per class accuracy. |

`update_op` | An operation that updates the accuracy tensor. |

Raises | |
---|---|

`ValueError` | If `predictions` and `labels` have mismatched shapes, or if `weights` is not `None` and its shape doesn't match `predictions` , or if either `metrics_collections` or `updates_collections` are not a list or tuple. |

`RuntimeError` | If eager execution is enabled. |

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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/r1.15/api_docs/python/tf/metrics/mean_per_class_accuracy