Method | Description | |
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FinishTraining ( ) : void | ||
Iteration ( ) : void |
Perform a single iteration.
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Iteration ( int iterations ) : void | ||
LearnBPROP ( double learningRate, double momentum ) : void |
Learn using backpropagation.
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LearnManhattan ( double learningRate ) : void |
Learn using the Manhattan update rule.
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LearnRPROP ( ) : void |
Learn using RPROP. Use default max step and initial update.
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LearnRPROP ( double initialUpdate, double maxStep ) : void |
Learn using RPROP with a custom initial update and max step.
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TrainFlatNetworkOpenCL ( |
Train a flat network multithreaded.
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Method | Description | |
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CallKernel ( int start, int size, bool learn, int iterations ) : void |
Call the kernel.
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GetOptions ( String learningType ) : String>.IDictionary |
Get the learning properties.
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public LearnBPROP ( double learningRate, double momentum ) : void | ||
learningRate | double | The learning rate. |
momentum | double | The momentum. |
return | void |
public LearnManhattan ( double learningRate ) : void | ||
learningRate | double | The learning rate. |
return | void |
public LearnRPROP ( double initialUpdate, double maxStep ) : void | ||
initialUpdate | double | The initial update value. |
maxStep | double | The max step. |
return | void |
public TrainFlatNetworkOpenCL ( |
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network | The network to train. | |
training | IEngineDataSet | The training data to use. |
profile | The OpenCL training profile. | |
return | Encog.Engine |