Computes the mean absolute error between the labels and predictions.
tf.compat.v1.metrics.mean_absolute_error( labels, predictions, weights=None, metrics_collections=None, updates_collections=None, name=None )
The mean_absolute_error
function creates two local variables, total
and count
that are used to compute the mean absolute error. This average is weighted by weights
, and it is ultimately returned as mean_absolute_error
: an idempotent operation that simply divides total
by count
.
For estimation of the metric over a stream of data, the function creates an update_op
operation that updates these variables and returns the mean_absolute_error
. Internally, an absolute_errors
operation computes the absolute value of the differences between predictions
and labels
. Then update_op
increments total
with the reduced sum of the product of weights
and absolute_errors
, and it increments count
with the reduced sum of weights
If weights
is None
, weights default to 1. Use weights of 0 to mask values.
Args | |
---|---|
labels | A Tensor of the same shape as predictions . |
predictions | A Tensor of arbitrary shape. |
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_absolute_error should be added to. |
updates_collections | An optional list of collections that update_op should be added to. |
name | An optional variable_scope name. |
Returns | |
---|---|
mean_absolute_error | A Tensor representing the current mean, the value of total divided by count . |
update_op | An operation that increments the total and count variables appropriately and whose value matches mean_absolute_error . |
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. |
© 2020 The TensorFlow Authors. All rights reserved.
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/compat/v1/metrics/mean_absolute_error