RMSProp optimizer
optimizer_rmsprop(lr = 0.001, rho = 0.9, epsilon = NULL, decay = 0, clipnorm = NULL, clipvalue = NULL)
| lr | float >= 0. Learning rate. |
|---|---|
| rho | float >= 0. Decay factor. |
| epsilon | float >= 0. Fuzz factor. If |
| 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. |
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.
Other optimizers: optimizer_adadelta,
optimizer_adagrad,
optimizer_adamax,
optimizer_adam,
optimizer_nadam,
optimizer_sgd