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Absolute loss, also known as L1-loss.

Accuracy loss, also known as zero-one-loss. This class provides exactly the same functionality as

but has a more intuitive name. Both classes are interchangeable.

Binary cross-entropy loss for multi-label problems, also known as logistic loss per output of a multi-label classifier.

Categorical cross-entropy loss for multi-class problems, also known as the logistic loss for softmax (categorical) outputs.

Euclidean loss, also known as zero-one-loss. This class provides exactly the same functionality as

but has a more intuitive name. Both classes are interchangeable.

Mean Accuracy loss, also known as zero-one-loss per class. Equivalent to

but for multi-label classifiers.

Negative log-likelihood loss.

Base class for

.

Base class for

.

R² (r-squared) loss.

Square loss, also known as L2-loss or Euclidean loss.

Accuracy loss, also known as zero-one-loss.

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