public class
BinaryCrossentropy
A Metric that computes the binary cross-entropy loss between true labels and predicted labels.
This is the crossentropy metric class to be used when there are only two label classes (0 and 1).
Inherited Constants
Public Constructors
BinaryCrossentropy(Ops tf, String name, boolean fromLogits, float labelSmoothing, long seed, Class<T> type)
Creates a BinaryCrossentropy metric
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Public Methods
Operand<T> |
Inherited Methods
Public Constructors
public BinaryCrossentropy (Ops tf, String name, boolean fromLogits, float labelSmoothing, long seed, Class<T> type)
Creates a BinaryCrossentropy metric
Parameters
tf | the TensorFlow Ops |
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name | the name of this metric, if null then metric name is getSimpleName() . |
fromLogits | Whether to interpret predictions as a tensor of logit values as opposed to a probability distribution. |
labelSmoothing | value used to smooth labels, When 0, no smoothing occurs. When > 0, compute the loss between the predicted labels and a smoothed version of the true labels, where the smoothing squeezes the labels towards 0.5. Larger values of label_smoothing correspond to heavier smoothing. |
seed | the seed for random number generation. An initializer created with a given seed will always produce the same random tensor for a given shape and data type. |
type | the type for the variables and result |