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tf.keras.metrics.FalseNegatives

Calculates the number of false negatives.

Inherits From: Metric

tf.keras.metrics.FalseNegatives(
    thresholds=None, name=None, dtype=None
)

Used in the notebooks

Used in the tutorials
Classification on imbalanced data

If sample_weight is given, calculates the sum of the weights of false negatives. This metric creates one local variable, accumulator that is used to keep track of the number of false negatives.

If sample_weight is None, weights default to 1. Use sample_weight of 0 to mask values.

Args
`thresholds`	(Optional) Defaults to `0.5`. A float value, or a Python list/tuple of float threshold values in `[0, 1]`. A threshold is compared with prediction values to determine the truth value of predictions (i.e., above the threshold is `True`, below is `False`). If used with a loss function that sets `from_logits=True` (i.e. no sigmoid applied to predictions), `thresholds` should be set to 0. One metric value is generated for each threshold value.
`name`	(Optional) string name of the metric instance.
`dtype`	(Optional) data type of the metric result.

Example:

m = keras.metrics.FalseNegatives()
m.update_state([0, 1, 1, 1], [0, 1, 0, 0])
m.result()
2.0

m.reset_state()
m.update_state([0, 1, 1, 1], [0, 1, 0, 0], sample_weight=[0, 0, 1, 0])
m.result()
1.0

Attributes
`dtype`
`variables`

Methods

`add_variable`

View source

add_variable(
    shape, initializer, dtype=None, aggregation='sum', name=None
)

`add_weight`

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add_weight(
    shape=(), initializer=None, dtype=None, name=None
)

`from_config`

View source

@classmethod
from_config(
    config
)

`get_config`

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get_config()

Return the serializable config of the metric.

`reset_state`

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reset_state()

Reset all of the metric state variables.

This function is called between epochs/steps, when a metric is evaluated during training.

`result`

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result()

Compute the current metric value.

Returns
A scalar tensor, or a dictionary of scalar tensors.

`stateless_reset_state`

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stateless_reset_state()

`stateless_result`

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stateless_result(
    metric_variables
)

`stateless_update_state`

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stateless_update_state(
    metric_variables, *args, **kwargs
)

`update_state`

View source

update_state(
    y_true, y_pred, sample_weight=None
)

Accumulates the metric statistics.

Args
`y_true`	The ground truth values.
`y_pred`	The predicted values.
`sample_weight`	Optional weighting of each example. Defaults to `1`. Can be a tensor whose rank is either 0, or the same rank as `y_true`, and must be broadcastable to `y_true`.

`call`

View source

__call__(
    *args, **kwargs
)

Call self as a function.

© 2022 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/keras/metrics/FalseNegatives