c

breeze.optimize.linear

ConjugateGradient

class ConjugateGradient[T, M] extends SerializableLogging

Solve argmin (a dot x + .5 * x dot (B * x) + .5 * normSquaredPenalty * (x dot x)) for x subject to norm(x) <= maxNormValue

Based on the code from "Trust Region Newton Method for Large-Scale Logistic Regression" * @author dlwh

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SerializableLogging, Serializable, Serializable, AnyRef, Any
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Instance Constructors

  1. new ConjugateGradient(maxNormValue: Double = Double.PositiveInfinity, maxIterations: Int = -1, normSquaredPenalty: Double = 0, tolerance: Double = 1E-5)(implicit space: MutableInnerProductVectorSpace[T, Double], mult: linalg.operators.OpMulMatrix.Impl2[M, T, T])

Type Members

  1. case class State extends Product with Serializable

Value Members

  1. final def !=(arg0: Any): Boolean
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  2. final def ##(): Int
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  5. def clone(): AnyRef
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  6. final def eq(arg0: AnyRef): Boolean
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  10. final def isInstanceOf[T0]: Boolean
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  11. def iterations(a: T, B: M, initX: T): Iterator[State]
  12. def logger: LazyLogger
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    protected
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  13. def minimize(a: T, B: M, initX: T): T
  14. def minimize(a: T, B: M): T
  15. def minimizeAndReturnResidual(a: T, B: M, initX: T): (T, T)

    Returns the vector x and the vector r.

    Returns the vector x and the vector r. x is the minimizer, while r is the residual error (which may not be near zero because of the norm constraint.)

  16. final def ne(arg0: AnyRef): Boolean
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  17. final def notify(): Unit
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  18. final def notifyAll(): Unit
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  19. final def synchronized[T0](arg0: ⇒ T0): T0
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  20. def toString(): String
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  21. final def wait(arg0: Long, arg1: Int): Unit
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Deprecated Value Members

  1. def finalize(): Unit
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    @Deprecated @deprecated @throws( classOf[java.lang.Throwable] )
    Deprecated

    (Since version ) see corresponding Javadoc for more information.

Inherited from SerializableLogging

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