- All Known Subinterfaces:
- All Known Implementing Classes:
- EarlyStoppingStrategy, EndIterationsStrategy, EndMaxErrorStrategy, EndMinutesStrategy, Greedy, HybridStrategy, RegularizationStrategy, RequiredImprovementStrategy, ResetStrategy, SmartLearningRate, SmartMomentum, StopTrainingStrategy
public interface StrategyTraining strategies can be added to training algorithms. Training strategies allow different additional logic to be added to an existing training algorithm. There are a number of different training strategies that can perform various tasks, such as adjusting the learning rate or momentum, or terminating training when improvement diminishes. Other strategies are provided as well.
void init(MLTrain train)Initialize this strategy.
train- The training algorithm.
void preIteration()Called just before a training iteration.
void postIteration()Called just after a training iteration.
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