ConjugateGradient

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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. def finalize(): Unit

   

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

   

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10. def getRegParam: Double

    

11. def hashCode(): Int

    

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12. final def isInstanceOf[T0]: Boolean

    

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13. var miniBatchFraction: Double

    

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    Definition Classes

    RegularizedOptimizer

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

    

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15. final def notify(): Unit

    

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16. final def notifyAll(): Unit

    

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17. var numIterations: Int

    

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    RegularizedOptimizer

18. def optimize(nPoints: Long, ParamOutEdges: Iterable[CausalEdge], initialP: DenseVector[Double]): DenseVector[Double]

    

    Find the optimum value of the parameters using Gradient Descent.

    Find the optimum value of the parameters using Gradient Descent.

    nPoints

    The number of data points

    ParamOutEdges

    An java.lang.Iterable object having all of the out edges of the parameter node

    initialP

    The initial value of the parameters as a DenseVector

    returns

    The value of the parameters as a DenseVector

    Definition Classes

    ConjugateGradient → Optimizer

19. var regParam: Double

    

    Attributes

    protected

    Definition Classes

    RegularizedOptimizer

20. def setMiniBatchFraction(fraction: Double): ConjugateGradient.this.type

    

    Set fraction of data to be used for each SGD iteration.

    Set fraction of data to be used for each SGD iteration. Default 1.0 (corresponding to deterministic/classical gradient descent)

    Definition Classes

    RegularizedOptimizer

21. def setNumIterations(iters: Int): ConjugateGradient.this.type

    

    Set the number of iterations for SGD.

    Set the number of iterations for SGD. Default 100.

    Definition Classes

    RegularizedOptimizer

22. def setRegParam(regParam: Double): ConjugateGradient.this.type

    

    Set the regularization parameter.

    Set the regularization parameter. Default 0.0.

    Definition Classes

    RegularizedOptimizer

23. def setStepSize(step: Double): ConjugateGradient.this.type

    

    Set the initial step size of SGD for the first step.

    Set the initial step size of SGD for the first step. Default 1.0. In subsequent steps, the step size will decrease with stepSize/sqrt(t)

    Definition Classes

    RegularizedOptimizer

24. var stepSize: Double

    

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    RegularizedOptimizer

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

    

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26. def toString(): String

    

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27. final def wait(): Unit

    

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

    

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

    

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