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org.tensorflow.framework.losses

Classes

BinaryCrossentropy Computes the cross-entropy loss between true labels and predicted labels.
CategoricalCrossentropy Computes the crossentropy loss between the labels and predictions.
CategoricalHinge Computes the categorical hinge loss between labels and predictions.
CosineSimilarity Computes the cosine similarity between labels and predictions.
Hinge Computes the hinge loss between labels and predictions.
Huber Computes the Huber loss between labels and predictions.
KLDivergence Computes Kullback-Leibler divergence loss between labels and predictions.
LogCosh Computes Computes the logarithm of the hyperbolic cosine of the prediction error.
Loss
Losses Built-in loss functions.
MeanAbsoluteError Computes the mean of absolute difference between labels and predictions.
MeanAbsolutePercentageError Computes the mean absolute percentage error between labels and predictions.
MeanSquaredError Computes the mean of squares of errors between labels and predictions.
MeanSquaredLogarithmicError Computes the mean squared logarithmic errors between labels and predictions.
Poisson Computes the Poisson loss between labels and predictions.
SparseCategoricalCrossentropy Computes the crossentropy loss between labels and predictions.
SquaredHinge Computes the squared hinge loss between labels and predictions.

Enums

Reduction Type of Loss Reduction

AUTO indicates that the reduction option will be determined by the usage context.