tf.compat.v1.metrics.true_negatives | TensorFlow v2.16.1 (original) (raw)
tf.compat.v1.metrics.true_negatives
Stay organized with collections Save and categorize content based on your preferences.
Sum the weights of true_negatives.
tf.compat.v1.metrics.true_negatives(
labels,
predictions,
weights=None,
metrics_collections=None,
updates_collections=None,
name=None
)
If weights is None, weights default to 1. Use weights of 0 to mask values.
| Args | |
|---|---|
| labels | The ground truth values, a Tensor whose dimensions must matchpredictions. Will be cast to bool. |
| predictions | The predicted values, a Tensor of arbitrary dimensions. Will be cast to bool. |
| weights | Optional Tensor whose rank is either 0, or the same rank aslabels, 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 the metric value variable should be added to. |
| updates_collections | An optional list of collections that the metric update ops should be added to. |
| name | An optional variable_scope name. |
| Returns | |
|---|---|
| value_tensor | A Tensor representing the current value of the metric. |
| update_op | An operation that accumulates the error from a batch of data. |
| Raises | |
|---|---|
| ValueError | If predictions and labels have mismatched shapes, or ifweights 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. |
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license.
Last updated 2024-04-26 UTC.