org.tensorflow.framework.losses
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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.
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Last updated 2021-11-29 UTC.
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