LossMetric
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Known Indirect Subclasses
BinaryCrossentropy<T extends TNumber>,
CategoricalCrossentropy<T extends TNumber>,
CategoricalHinge<T extends TNumber>,
CosineSimilarity<T extends TNumber>,
Hinge<T extends TNumber>,
KLDivergence<T extends TNumber>,
LogCoshError<T extends TNumber>,
MeanAbsoluteError<T extends TNumber>,
MeanAbsolutePercentageError<T extends TNumber>,
MeanSquaredError<T extends TNumber>,
MeanSquaredLogarithmicError<T extends TNumber>,
Poisson<T extends TNumber>,
SparseCategoricalCrossentropy<T extends TNumber>,
SquaredHinge<T extends TNumber>
| BinaryCrossentropy<T extends TNumber> |
A Metric that computes the binary cross-entropy loss between true labels and predicted labels. |
| CategoricalCrossentropy<T extends TNumber> |
A Metric that computes the categorical cross-entropy loss between true labels and predicted
labels. |
| CategoricalHinge<T extends TNumber> |
A Metric that computes the categorical hinge loss metric between labels and predictions. |
| CosineSimilarity<T extends TNumber> |
A metric that computes the cosine similarity metric between labels and predictions. |
| Hinge<T extends TNumber> |
A metric that computes the hinge loss metric between labels and predictions. |
| KLDivergence<T extends TNumber> |
A metric that computes the Kullback-Leibler divergence loss metric between labels and
predictions. |
| LogCoshError<T extends TNumber> |
A metric that computes the logarithm of the hyperbolic cosine of the prediction error metric
between labels and predictions. |
| MeanAbsoluteError<T extends TNumber> |
A metric that computes the mean of absolute difference between labels and predictions. |
| MeanAbsolutePercentageError<T extends TNumber> |
A metric that computes the mean of absolute difference between labels and predictions. |
| MeanSquaredError<T extends TNumber> |
A metric that computes the mean of absolute difference between labels and predictions. |
| MeanSquaredLogarithmicError<T extends TNumber> |
A metric that computes the mean of absolute difference between labels and predictions. |
| Poisson<T extends TNumber> |
A metric that computes the poisson loss metric between labels and predictions. |
| SparseCategoricalCrossentropy<T extends TNumber> |
A metric that computes the sparse categorical cross-entropy loss between true labels and
predicted labels. |
| SquaredHinge<T extends TNumber> |
A metric that computes the squared hinge loss metric between labels and predictions. |
|
Interface for Metrics that wrap Loss functions.
Public Methods
public
abstract
Operand<T>
call
(Operand<? extends TNumber> labels, Operand<? extends TNumber> predictions)
Calculates the weighted loss between labels and predictions
Parameters
| labels |
the truth values or labels |
| predictions |
the predictions |
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Last updated 2021-11-29 UTC.
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