tf.keras.metrics.BinaryAccuracy

Calculates how often predictions match binary labels.

Inherits From: MeanMetricWrapper, Mean, Metric

Used in the notebooks

Used in the tutorials

This metric creates two local variables, total and count that are used to compute the frequency with which y_pred matches y_true. This frequency is ultimately returned as binary accuracy: an idempotent operation that simply divides total by count.

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

name (Optional) string name of the metric instance.
dtype (Optional) data type of the metric result.
threshold (Optional) Float representing the threshold for deciding whether prediction values are 1 or 0.

Example:

m = keras.metrics.BinaryAccuracy()
m.update_state([[1], [1], [0], [0]], [[0.98], [1], [0], [0.6]])
m.result()
0.75
m.reset_state()
m.update_state([[1], [1], [0], [0]], [[0.98], [1], [0], [0.6]],
               sample_weight=[1, 0, 0, 1])
m.result()
0.5

Usage with compile() API:

model.compile(optimizer='sgd',
              loss='binary_crossentropy',
              metrics=[keras.metrics.BinaryAccuracy()])

dtype

variables

Methods

add_variable

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add_weight

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from_config

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get_config

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Return the serializable config of the metric.

reset_state

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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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Compute the current metric value.

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

stateless_reset_state

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stateless_result

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stateless_update_state

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update_state

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Accumulate statistics for the metric.

__call__

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Call self as a function.