tf.keras.metrics.TruePositives

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Class TruePositives

免费成长做爱直播有哪些Calculates the number of true positives.

Aliases:

  • Class tf.compat.v1.keras.metrics.TruePositives
  • Class tf.compat.v2.keras.metrics.TruePositives
  • Class tf.compat.v2.metrics.TruePositives
  • Class tf.metrics.TruePositives

For example, if y_true is [0, 1, 1, 1] and y_pred is [1, 0, 1, 1] then the true positives value is 2. If the weights were specified as [0, 0, 1, 0] then the true positives value would be 1.

If sample_weight is given, calculates the sum of the weights of true positives. This metric creates one local variable, true_positives that is used to keep track of the number of true positives.

If sample_weight is None, weights default to 1. Use sample_weight免费成长做爱直播有哪些 of 0 to mask values.

Usage:

m = tf.keras.metrics.TruePositives()
m.update_state([0, 1, 1, 1], [1, 0, 1, 1])
print('Final result: ', m.result().numpy())  # Final result: 2

Usage with tf.keras API:

model = tf.keras.Model(inputs, outputs)
model.compile('sgd', loss='mse', metrics=[tf.keras.metrics.TruePositives()])

__init__

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__init__(
    thresholds=None,
    name=None,
    dtype=None
)

Creates a TruePositives instance.

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). 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.

Methods

reset_states

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reset_states()

免费成长做爱直播有哪些Resets 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()

免费成长做爱直播有哪些Computes and returns the metric value tensor.

免费成长做爱直播有哪些Result computation is an idempotent operation that simply calculates the metric value using the state variables.

update_state

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update_state(
    y_true,
    y_pred,
    sample_weight=None
)

免费成长做爱直播有哪些Accumulates the given confusion matrix condition 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.

Returns:

Update op.

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