View source on GitHub |
Calculates how often predictions
matches labels
.
tf.compat.v1.metrics.accuracy(
labels, predictions, weights=None, metrics_collections=None,
updates_collections=None, name=None
)
The accuracy
function creates two local variables, total
and
count
that are used to compute the frequency with which predictions
matches labels
. This frequency is ultimately returned as accuracy
: 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 accuracy
.
Internally, an is_correct
operation computes a Tensor
with elements 1.0
where the corresponding elements of predictions
and labels
match and 0.0
otherwise. Then update_op
increments total
with the reduced sum of the
product of weights
and is_correct
, 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
|
The ground truth values, a Tensor whose shape matches
predictions .
|
predictions
|
The predicted values, a Tensor of any 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 accuracy 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 | |
---|---|
accuracy
|
A Tensor representing the accuracy, the value of total divided
by count .
|
update_op
|
An operation that increments the total and count variables
appropriately and whose value matches accuracy .
|
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. |