Class/Object

org.apache.flink.ml.optimization

IterativeSolver

Related Docs: object IterativeSolver | package optimization

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abstract class IterativeSolver extends Solver

An abstract class for iterative optimization algorithms

See Iterative Methods on Wikipedia for more info

Linear Supertypes
Solver, WithParameters, Serializable, Serializable, AnyRef, Any
Known Subclasses
GradientDescent
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Inherited
  1. IterativeSolver
  2. Solver
  3. WithParameters
  4. Serializable
  5. Serializable
  6. AnyRef
  7. Any
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Visibility
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Instance Constructors

  1. new IterativeSolver()

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Abstract Value Members

  1. abstract def optimize(data: DataSet[LabeledVector], initialWeights: Option[DataSet[WeightVector]]): DataSet[WeightVector]

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    Provides a solution for the given optimization problem

    Provides a solution for the given optimization problem

    data

    A Dataset of LabeledVector (input, output) pairs

    initialWeights

    The initial weight that will be optimized

    returns

    A Vector of weights optimized to the given problem

    Definition Classes
    Solver

Concrete Value Members

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

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    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any

  3. final def ==(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  4. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  5. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  6. def createInitialWeightVector(dimensionDS: DataSet[Int]): DataSet[WeightVector]

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    Creates a DataSet with one zero vector.

    Creates a DataSet with one zero vector. The zero vector has dimension d, which is given by the dimensionDS.

    dimensionDS

    DataSet with one element d, denoting the dimension of the returned zero vector

    returns

    DataSet of a zero vector of dimension d

    Definition Classes
    Solver

  7. def createInitialWeightsDS(initialWeights: Option[DataSet[WeightVector]], data: DataSet[LabeledVector]): DataSet[WeightVector]

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    Creates initial weights vector, creating a DataSet with a WeightVector element

    Creates initial weights vector, creating a DataSet with a WeightVector element

    initialWeights

    An Option that may contain an initial set of weights

    data

    The data for which we optimize the weights

    returns

    A DataSet containing a single WeightVector element

    Definition Classes
    Solver

  8. final def eq(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef

  9. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  10. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

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

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    Definition Classes
    AnyRef → Any

  12. def hashCode(): Int

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    Definition Classes
    AnyRef → Any

  13. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

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

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    Definition Classes
    AnyRef

  15. final def notify(): Unit

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    Definition Classes
    AnyRef

  16. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

  17. val parameters: ParameterMap

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    Definition Classes
    WithParameters

  18. def setConvergenceThreshold(convergenceThreshold: Double): IterativeSolver.this.type

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  19. def setIterations(iterations: Int): IterativeSolver.this.type

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  20. def setLearningRateMethod(learningRateMethod: LearningRateMethodTrait): IterativeSolver.this.type

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  21. def setLossFunction(lossFunction: LossFunction): IterativeSolver.this.type

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    Definition Classes
    Solver

  22. def setRegularizationConstant(regularizationConstant: Double): IterativeSolver.this.type

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    Definition Classes
    Solver

  23. def setRegularizationPenalty(regularizationPenalty: RegularizationPenalty): IterativeSolver.this.type

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    Definition Classes
    Solver

  24. def setStepsize(stepsize: Double): IterativeSolver.this.type

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

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    Definition Classes
    AnyRef

  26. def toString(): String

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    Definition Classes
    AnyRef → Any

  27. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Solver

Inherited from WithParameters

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped