Contains a set of training options. More...
#include <SimdNeural.hpp>
Public Types | |
enum | InitType { Xavier } |
enum | LossType { Mse , CrossEntropy , CrossEntropyMulticlass } |
enum | UpdateType { AdaptiveGradient } |
Public Member Functions | |
TrainOptions () | |
Default constructor. | |
Data Fields | |
InitType | initType |
Method to initialize weights. | |
LossType | lossType |
Loss function type. | |
UpdateType | updateType |
Weights' update type. | |
size_t | threadNumber |
Number of threads used to train. Use -1 to auto detect thread number. | |
size_t | epochStart |
Start epoch. It is used to continue training process. | |
size_t | epochFinish |
Finish epoch. Describes total epoch number. | |
size_t | batchSize |
A batch size. | |
float | alpha |
Describes training speed. | |
float | epsilon |
Used to prevent division by zero. | |
bool | shuffle |
A flag to shuffle training set. | |
Detailed Description
Contains a set of training options.
Member Enumeration Documentation
◆ InitType
enum InitType |
◆ LossType
enum LossType |
◆ UpdateType
enum UpdateType |
Method of weights' updating.
Enumerator | |
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AdaptiveGradient | Adaptive gradients method. J Duchi, E Hazan and Y Singer, "Adaptive subgradient methods for online learning and stochastic optimization" The Journal of Machine Learning Research, pages 2121-2159, 2011.
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