R Loss Function

• R Loss Function Formula
• R Loss Function Excel
• R Custom Loss Function
• R Glm Loss Function
• Loss Function In R

Loss functions can be specified either using the name of a built in loss function (e.g. 'loss = binarycrossentropy'), a reference to a built in loss function (e.g. 'loss = lossbinarycrossentropy') or by passing an artitrary function that returns a scalar for each data-point and takes the following two arguments. If 'gaussian' fitting is by least-squares, and if 'symmetric' a re-descending M estimator is used with Tukey's biweight function. Can be abbreviated. Fit the model or just extract the model frame. Can be abbreviated. Control parameters: see loess.control.

Model loss functions

R Loss Function Formula

Arguments

R Loss Function Excel

Details

Loss functions are to be supplied in the loss parameter of thecompile.keras.engine.training.Model() function.

R Custom Loss Function

Loss functions can be specified either using the name of a built in lossfunction (e.g. 'loss = binary_crossentropy'), a reference to a built in lossfunction (e.g. 'loss = loss_binary_crossentropy()') or by passing anartitrary function that returns a scalar for each works mostlylike the mean squared error, but will not be so strongly affected by theoccasional wildly incorrect prediction. However, it may return NaNs if theintermediate value cosh(y_pred - y_true) is too large to be representedin the chosen precision.

R Glm Loss Function

See also

Loss Function In R

compile.keras.engine.training.Model(), loss_binary_crossentropy()