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Module: tfr.keras.losses

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Keras losses in TF-Ranking.

Classes

class ApproxMRRLoss: Computes approximate MRR loss between y_true and y_pred.

class ApproxNDCGLoss: Computes approximate NDCG loss between y_true and y_pred.

class ClickEMLoss: Computes click EM loss between y_true and y_pred.

class DCGLambdaWeight: Keras serializable class for DCG.

class GumbelApproxNDCGLoss: Computes the Gumbel approximate NDCG loss between y_true and y_pred.

class LabelDiffLambdaWeight: Keras serializable class for LabelDiffLambdaWeight.

class ListMLELambdaWeight: LambdaWeight for ListMLE cost function.

class ListMLELoss: Computes ListMLE loss between y_true and y_pred.

class MeanSquaredLoss: Computes mean squared loss between y_true and y_pred.

class MixtureEMLoss: Computes mixture EM loss between y_true and y_pred.

class NDCGLambdaWeight: Keras serializable class for NDCG.

class NDCGLambdaWeightV2: Keras serializable class for NDCG LambdaWeight V2 for topn.

class OrdinalLoss: Computes the Ordinal loss between y_true and y_pred.

class PairwiseHingeLoss: Computes pairwise hinge loss between y_true and y_pred.

class PairwiseLogisticLoss: Computes pairwise logistic loss between y_true and y_pred.

class PairwiseMSELoss: Computes pairwise mean squared error loss between y_true and y_pred.

class PairwiseSoftZeroOneLoss: Computes pairwise soft zero-one loss between y_true and y_pred.

class PrecisionLambdaWeight: Keras serializable class for Precision.

class RankingLossKey: Ranking loss key strings.

class SigmoidCrossEntropyLoss: Computes the Sigmoid cross-entropy loss between y_true and y_pred.

class SoftmaxLoss: Computes Softmax cross-entropy loss between y_true and y_pred.

class UniqueSoftmaxLoss: Computes unique softmax cross-entropy loss between y_true and y_pred.

Functions

get(...): Factory method to get a ranking loss class.