Package | Description |
---|---|
org.nd4j.linalg.api.ops.impl.loss |
Modifier and Type | Class and Description |
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class |
AbsoluteDifferenceLoss
Absolute difference loss
|
class |
CosineDistanceLoss
Cosine distance loss
|
class |
HingeLoss
Hinge loss
|
class |
HuberLoss
Huber loss
|
class |
LogLoss
Binary log loss, or cross entropy loss:
-1/numExamples * sum_i (labels[i] * log(predictions[i] + epsilon) + (1-labels[i]) * log(1-predictions[i] + epsilon)) |
class |
LogPoissonLoss
Log Poisson loss
Note: This expects that the input/predictions are log(x) not x!
|
class |
MeanPairwiseSquaredErrorLoss
Mean Pairwise Squared Error Loss
|
class |
MeanSquaredErrorLoss
Mean squared error loss
|
class |
SigmoidCrossEntropyLoss
Sigmoid cross entropy loss with logits
|
class |
SoftmaxCrossEntropyLoss
Softmax cross entropy loss
|
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