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`