tf.compat.v1.metrics.mean_absolute_error

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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 asmean_absolute_error: an idempotent operation that simply divides total bycount.

For estimation of the metric over a stream of data, the function creates anupdate_op operation that updates these variables and returns themean_absolute_error. Internally, an absolute_errors operation computes the absolute value of the differences between predictions and labels. Thenupdate_op increments total with the reduced sum of the product ofweights 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 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 thatmean_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 oftotal 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 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.

tf.compat.v1.metrics.mean_absolute_error | TensorFlow v2.16.1 (original) (raw)