Class

com.danylchuk.swiftlearner.nn.backprop

BackpropClassifier

Related Doc: package backprop

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class BackpropClassifier extends AnyRef

A convenience shortcut for applying BackpropNet to classification problems.

Assumes consecutive class indices 0..N

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Instance Constructors

  1. new BackpropClassifier(trainingSet: Seq[(Int, Seq[Float])], nHidden: Int, nTimes: Int, learnRate: Float = 1.0f, normalize: (Float) ⇒ Float = identity, seed: Option[Long] = None)

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    trainingSet

    A sequence of entries: (class: Int, parameters: Seq[Float])

    nHidden

    Number of hidden nodes

    nTimes

    Number of times to repeat the training sequence

    normalize

    Optional normalization function to speed up learning

Value Members

  1. final def !=(arg0: Any): Boolean

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  2. final def ##(): Int

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  3. final def ==(arg0: Any): Boolean

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  4. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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  6. final def eq(arg0: AnyRef): Boolean

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  7. def equals(arg0: Any): Boolean

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  8. val examples: Seq[(Array[Float], Array[Float])]

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  9. def finalize(): Unit

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  10. final def getClass(): Class[_]

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  11. def hashCode(): Int

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  12. final def isInstanceOf[T0]: Boolean

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  13. val learned: BackpropNet

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  14. val nClasses: Int

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  15. val nParams: Int

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  16. final def ne(arg0: AnyRef): Boolean

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  17. val nn: BackpropNet

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  18. final def notify(): Unit

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  19. final def notifyAll(): Unit

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  20. def predict(parameters: Seq[Float]): Int

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    Predicts the most likely class given the parameters.

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

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  22. def toString(): String

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  23. final def wait(): Unit

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

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

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