Package org.nd4j.linalg.lossfunctions.impl

Class Summary

Class	Description
LossBinaryXENT	Binary cross entropy loss function https://en.wikipedia.org/wiki/Cross_entropy#Cross-entropy_error_function_and_logistic_regression Labels are assumed to take values 0 or 1
LossCosineProximity	Created by susaneraly on 9/9/16.
LossFMeasure	F–measure loss function is a loss function design for training on imbalanced datasets.
LossHinge	Created by susaneraly on 8/15/16.
LossKLD	Kullback Leibler Divergence loss function
LossL1	L1 loss function: i.e., sum of absolute errors, L = sum_i abs(predicted_i - actual_i) See also LossMAE for a mathematically similar loss function (MAE has division by N, where N is output size)
LossL2	L2 loss function: i.e., sum of squared errors, L = sum_i (actual_i - predicted)^2 The L2 loss function is the square of the L2 norm of the difference between actual and predicted.
LossMAE	Mean absolute error loss function: L = 1/N sum_i abs(predicted_i - actual_i) See also LossL1 for a mathematically similar loss function (LossL1 does not have division by N, where N is output size)
LossMAPE	Created by susaneraly on 8/15/16.
LossMCXENT	Multi-Class Cross Entropy loss function: L = sum_i actual_i * log( predicted_i )
LossMixtureDensity	This is a cost function associated with a mixture-density network.
LossMixtureDensity.Builder
LossMixtureDensity.MixtureDensityComponents	This class is a data holder for the mixture density components for convenient manipulation.
LossMSE	Mean Squared Error loss function: L = 1/N sum_i (actual_i - predicted)^2 See also LossL2 for a mathematically similar loss function (LossL2 does not have division by N, where N is output size)
LossMSLE	Mean Squared Logarithmic Error loss function: L = 1/N sum_i (log(1+predicted_i) - log(1+actual_i))^2
LossMultiLabel	Multi-Label-Loss Function, maybe more commonly known as BPMLL
LossNegativeLogLikelihood	Negative log likelihood loss function
LossPoisson	Created by susaneraly on 9/9/16.
LossSquaredHinge	Created by susaneraly on 9/9/16.
LossWasserstein	Wasserstein loss function, which calculates the Wasserstein distance, also known as earthmover's distance.