Class/Object

org.apache.spark.mllib.optimization

LBFGS

Related Docs: object LBFGS | package optimization

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class LBFGS extends Optimizer with Logging

:: DeveloperApi :: Class used to solve an optimization problem using Limited-memory BFGS. Reference: Wikipedia on Limited-memory BFGS

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@DeveloperApi()
Source
LBFGS.scala
Linear Supertypes
Logging, Optimizer, Serializable, Serializable, AnyRef, Any
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  1. LBFGS
  2. Logging
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Visibility
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Instance Constructors

  1. new LBFGS(gradient: Gradient, updater: Updater)

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    gradient

    Gradient function to be used.

    updater

    Updater to be used to update weights after every iteration.

Value Members

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

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    Definition Classes
    AnyRef → Any
  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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    Attributes
    protected[java.lang]
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    @throws( ... )
  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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    protected[java.lang]
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    @throws( classOf[java.lang.Throwable] )
  9. final def getClass(): Class[_]

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  10. def hashCode(): Int

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  11. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean = false): Boolean

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    Attributes
    protected
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    Logging
  12. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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    Attributes
    protected
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    Logging
  13. final def isInstanceOf[T0]: Boolean

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    Any
  14. def isTraceEnabled(): Boolean

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    Attributes
    protected
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    Logging
  15. def log: Logger

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    protected
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    Logging
  16. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

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    protected
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    Logging
  17. def logDebug(msg: ⇒ String): Unit

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    protected
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    Logging
  18. def logError(msg: ⇒ String, throwable: Throwable): Unit

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    protected
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    Logging
  19. def logError(msg: ⇒ String): Unit

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    protected
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    Logging
  20. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

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    Logging
  21. def logInfo(msg: ⇒ String): Unit

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    Logging
  22. def logName: String

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    Logging
  23. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

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    Logging
  24. def logTrace(msg: ⇒ String): Unit

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    Logging
  25. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

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    protected
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    Logging
  26. def logWarning(msg: ⇒ String): Unit

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    protected
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    Logging
  27. final def ne(arg0: AnyRef): Boolean

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    AnyRef
  28. final def notify(): Unit

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  29. final def notifyAll(): Unit

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    AnyRef
  30. def optimize(data: RDD[(Double, Vector)], initialWeights: Vector): Vector

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    Solve the provided convex optimization problem.

    Solve the provided convex optimization problem.

    Definition Classes
    LBFGSOptimizer
  31. def setConvergenceTol(tolerance: Double): LBFGS.this.type

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    Set the convergence tolerance of iterations for L-BFGS.

    Set the convergence tolerance of iterations for L-BFGS. Default 1E-6. Smaller value will lead to higher accuracy with the cost of more iterations. This value must be nonnegative. Lower convergence values are less tolerant and therefore generally cause more iterations to be run.

  32. def setGradient(gradient: Gradient): LBFGS.this.type

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    Set the gradient function (of the loss function of one single data example) to be used for L-BFGS.

  33. def setNumCorrections(corrections: Int): LBFGS.this.type

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    Set the number of corrections used in the LBFGS update.

    Set the number of corrections used in the LBFGS update. Default 10. Values of numCorrections less than 3 are not recommended; large values of numCorrections will result in excessive computing time. numCorrections must be positive, and values from 4 to 9 are generally recommended.

  34. def setNumIterations(iters: Int): LBFGS.this.type

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    Set the maximal number of iterations for L-BFGS.

    Set the maximal number of iterations for L-BFGS. Default 100.

  35. def setRegParam(regParam: Double): LBFGS.this.type

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    Set the regularization parameter.

    Set the regularization parameter. Default 0.0.

  36. def setUpdater(updater: Updater): LBFGS.this.type

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    Set the updater function to actually perform a gradient step in a given direction.

    Set the updater function to actually perform a gradient step in a given direction. The updater is responsible to perform the update from the regularization term as well, and therefore determines what kind or regularization is used, if any.

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

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  38. def toString(): String

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  39. final def wait(): Unit

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    @throws( ... )
  40. final def wait(arg0: Long, arg1: Int): Unit

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    @throws( ... )
  41. final def wait(arg0: Long): Unit

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Inherited from Logging

Inherited from Optimizer

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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