optimizer_rmsprop

0th

Percentile

RMSProp optimizer

RMSProp optimizer

Usage
optimizer_rmsprop(lr = 0.001, rho = 0.9, epsilon = 1e-08, decay = 0,
  clipnorm = NULL, clipvalue = NULL)
Arguments
lr

float >= 0. Learning rate.

rho

float >= 0. Decay factor.

epsilon

float >= 0. Fuzz factor.

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.

Note

It is recommended to leave the parameters of this optimizer at their default values (except the learning rate, which can be freely tuned).

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

Aliases
  • optimizer_rmsprop
Documentation reproduced from package keras, version 2.1.3, License: MIT + file LICENSE

Community examples

Looks like there are no examples yet.