# tf.keras.metrics.binary_accuracy

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|---|---|
| [![](https://www.tensorflow.org/images/tf_logo_32px.png) TensorFlow 1 version](https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/keras/metrics/binary_accuracy) | [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.2.0/tensorflow/python/keras/metrics.py#L3187-L3202) |

Calculates how often predictions matches binary labels.

#### View aliases


**Main aliases**

[`tf.metrics.binary_accuracy`](https://www.tensorflow.org/api_docs/python/tf/keras/metrics/binary_accuracy)
**Compat aliases for migration**

See
[Migration guide](https://www.tensorflow.org/guide/migrate) for
more details.

[`tf.compat.v1.keras.metrics.binary_accuracy`](https://www.tensorflow.org/api_docs/python/tf/keras/metrics/binary_accuracy)

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    tf.keras.metrics.binary_accuracy(
        y_true, y_pred, threshold=0.5
    )

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| ## Args ||
|---|---|
| `y_true` | Ground truth values. shape = `[batch_size, d0, .. dN]`. |
| `y_pred` | The predicted values. shape = `[batch_size, d0, .. dN]`. |
| `threshold` | (Optional) Float representing the threshold for deciding whether prediction values are 1 or 0. |

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| ## Returns ||
|---|---|
| Binary accuracy values. shape = `[batch_size, d0, .. dN-1]` ||

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