tf.metrics.percentage_below
tf.metrics.percentage_below
tf.metrics.percentage_below
percentage_below( values, threshold, weights=None, metrics_collections=None, updates_collections=None, name=None )
Defined in tensorflow/python/ops/metrics_impl.py
.
Computes the percentage of values less than the given threshold.
The percentage_below
function creates two local variables, total
and count
that are used to compute the percentage of values
that fall below threshold
. This rate is weighted by weights
, and it is ultimately returned as percentage
which is 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 percentage
.
If weights
is None
, weights default to 1. Use weights of 0 to mask values.
Args:
-
values
: A numericTensor
of arbitrary size. -
threshold
: A scalar threshold. -
weights
: OptionalTensor
whose rank is either 0, or the same rank asvalues
, and must be broadcastable tovalues
(i.e., all dimensions must be either1
, or the same as the correspondingvalues
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:
-
percentage
: ATensor
representing the current mean, the value oftotal
divided bycount
. -
update_op
: An operation that increments thetotal
andcount
variables appropriately.
Raises:
-
ValueError
: Ifweights
is notNone
and its shape doesn't matchvalues
, or if eithermetrics_collections
orupdates_collections
are not a list or tuple.
© 2017 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/api_docs/python/tf/metrics/percentage_below