org.apache.spark.streamdm.classifiers.model

Loss

trait Loss extends Serializable

A Loss trait defines the operation needed to compute the loss function, the prediction function, and the gradient for use in a LinearModel.

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Serializable, Serializable, AnyRef, Any
Known Subclasses
HingeLoss, LogisticLoss, PerceptronLoss, SquaredLoss
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Abstract Value Members

  1. abstract def gradient(label: Double, dot: Double): Double

    Computes the value of the gradient function

    Computes the value of the gradient function

    dot

    the dot product of the linear model and the instance

    returns

    the gradient value

  2. abstract def loss(label: Double, dot: Double): Double

    Computes the value of the loss function

    Computes the value of the loss function

    dot

    the dot product of the linear model and the instance

    returns

    the loss value

  3. abstract def predict(dot: Double): Double

    Computes the binary prediction based on a dot product

    Computes the binary prediction based on a dot product

    dot

    the dot product of the linear model and the instance

    returns

    the predicted binary class

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

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

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  3. final def ##(): Int

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

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  15. final def notify(): Unit

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  16. final def notifyAll(): Unit

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  17. def prob(dot: Double): Double

    Computes the probability of a binary prediction based on a dot product

    Computes the probability of a binary prediction based on a dot product

    dot

    the dot product of the linear model and the instance

    returns

    the predicted probability

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

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  19. def toString(): String

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  20. final def wait(): Unit

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