huber_loss: Huber loss

In stschn/deepANN: Neural Network Toolbox

Huber loss

Description

Huber loss

Usage

huber_loss(actuals, preds, delta = 1, na.rm = FALSE)

Arguments

actuals	A numeric vector of actual values.
preds	A numeric vector of prediction values.
delta	A parameter that shows the error difference and controls the calculation.
na.rm	A logical value indicating whether actual and prediction pairs with at least one NA value should be ignored.

Details

Huber loss is less sensitive to outliers than MSE.

Value

Huber loss.

References

Huber, Peter J. (1964): Robust Estimation of a Location Parameter. In: Annals of Mathematical Statistics, 35 (1964) 1, 73-101. Hasti, Trevor; Tibshirani, Robert; Friedman, Jerome (2009): The Elements of Statistical Learning. 2nd ed., 2009. New York: Springer. (p. 349).

See Also

Other Metrics: accuracy(), cross_entropy(), dice(), entropy(), erf(), erfc(), erfcinv(), erfinv(), gini_impurity(), iou(), log_cosh_loss(), mae(), mape(), mse(), msle(), quantile_loss(), rmse(), rmsle(), rmspe(), sse(), stderror(), vc(), wape(), wmape()

stschn/deepANN documentation built on June 25, 2024, 7:27 a.m.