optimizer_rmsprop: RMSProp optimizer

In SPOTMisc: Misc Extensions for the 'SPOT' Package

RMSProp optimizer

Description

RMSProp optimizer

Usage

optimizer_rmsprop(
  learning_rate = 0.001,
  rho = 0.9,
  epsilon = NULL,
  decay = 0,
  clipnorm = NULL,
  clipvalue = NULL,
  ...
)

Arguments

learning_rate	float >= 0. Learning rate.
rho	float >= 0. Decay factor.
epsilon	float >= 0. Fuzz factor. If 'NULL', defaults to 'k_epsilon()'.
decay	float >= 0. Learning rate decay over each update.
clipnorm	Gradients will be clipped when their L2 norm exceeds this value.
clipvalue	Gradients will be clipped when their absolute value exceeds this value.
...	Unused, present only for backwards compatability

Note

This optimizer is usually a good choice for recurrent neural networks.

See Also

Other optimizers: optimizer_adadelta(), optimizer_adagrad(), optimizer_adamax(), optimizer_adam(), optimizer_nadam(), optimizer_sgd()

SPOTMisc documentation built on Sept. 5, 2022, 5:06 p.m.