org.kramerlab.autoencoder.neuralnet.rbm

RandomRetryTrainingStrategy

class RandomRetryTrainingStrategy extends RbmTrainingStrategy

This training strategy generates multiple Rbm training configurations at random, and selects the Rbm which has best reconstruction error on a held out validation set.

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Instance Constructors

  1. new RandomRetryTrainingStrategy(numRetries: Int, relativeValidationSetSize: Double)

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  17. final def synchronized[T0](arg0: ⇒ T0): T0

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  18. def toString(): String

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  19. def train(rbm: Rbm, data: Mat, trainingObservers: List[TrainingObserver]): Rbm

    Definition Classes
    RandomRetryTrainingStrategy → RbmTrainingStrategy

  20. final def wait(): Unit

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  21. final def wait(arg0: Long, arg1: Int): Unit

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  22. final def wait(arg0: Long): Unit

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Inherited from RbmTrainingStrategy

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