Package org.tensorflow.framework.losses

package org.tensorflow.framework.losses

Class	Description
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	Interface for loss calc ulation
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.
Reduction	Type of AbstractLoss Reduction
SparseCategoricalCrossentropy	Computes the crossentropy loss between labels and predictions.
SquaredHinge	Computes the squared hinge loss between labels and predictions.