com.github.bruneli.scalaopt.core.gradient

ConjugateGradient

object ConjugateGradient extends Optimizer[ObjectiveFunction, CGConfig]

Implements the non-linear conjugate gradient method.

This algorithm is described in Chapter 5 of: "J. Nocedal, S.J. Wright, Numerical Optimization, Springer."

scala> import com.github.bruneli.scalaopt.core._
scala> import gradient.ConjugateGradient._
scala> minimize((x: Variables) => x dot x, Vector(2.0, 4.0)) // Approximate derivatives
scala> minimize(((x: Variables) => x dot x, (x: Variables) => x * 2.0), Vector(2.0, 4.0)) // Exact derivatives
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Optimizer[ObjectiveFunction, CGConfig], AnyRef, Any
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  7. def beta(dfk: Variables, dfkpp: Variables, method: String): Double

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  9. implicit val defaultConfig: CGConfig

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    ConjugateGradient → Optimizer

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  16. def minimize(f: ObjectiveFunction, x0: Variables)(implicit pars: CGConfig): Try[Variables]

    Minimize an objective function acting on a vector of real values.

    Minimize an objective function acting on a vector of real values.

    f

    real-valued objective function

    x0

    initial Variables

    pars

    algorithm configuration parameters

    returns

    Variables at a local minimum

    Definition Classes
    ConjugateGradient → Optimizer

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

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  18. final def notify(): Unit

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  19. final def notifyAll(): Unit

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