Adagrad optimizer.
Adagrad optimizer as described in Adaptive Subgradient Methods for OnlineLearning and StochasticOptimization.
optimizer_adagrad(lr = 0.01, epsilon = NULL, decay = 0, clipnorm = NULL,
clipvalue = NULL)Arguments
| lr | float >= 0. Learning rate. |
| 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. |
Note
It is recommended to leave the parameters of this optimizer at their default values.
See also
Other optimizers: optimizer_adadelta,
optimizer_adamax,
optimizer_adam,
optimizer_nadam,
optimizer_rmsprop,
optimizer_sgd