Class

org.ada.server.runnables.core

RunRowTimeSeriesRCRegressionSpec

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case class RunRowTimeSeriesRCRegressionSpec(dataSetId: String, inputFieldNames: Seq[String], outputFieldName: String, orderFieldName: String, orderedStringValues: Seq[String], criterionFieldName: String, criterionStringValue: String, predictAhead: Int, mlModelId: BSONObjectID, windowSize: Option[Int], reservoirNodeNum: ValueOrSeq[Int] = Left(None), reservoirInDegree: ValueOrSeq[Int] = Left(None), reservoirEdgesNum: ValueOrSeq[Int] = Left(None), reservoirPreferentialAttachment: Boolean = false, reservoirBias: Boolean = false, reservoirCircularInEdges: Option[Seq[Int]] = None, inputReservoirConnectivity: ValueOrSeq[Double] = Left(None), reservoirSpectralRadius: ValueOrSeq[Double] = Left(None), reservoirFunctionType: ActivationFunctionType, reservoirFunctionParams: Seq[Double] = Nil, washoutPeriod: ValueOrSeq[Int] = Left(None), learningSetting: RegressionLearningSetting, minCrossValidationTrainingSizeRatio: Option[Double], trainingTestSplitOrderValue: Option[Double]) extends Product with Serializable

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  1. RunRowTimeSeriesRCRegressionSpec
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Instance Constructors

  1. new RunRowTimeSeriesRCRegressionSpec(dataSetId: String, inputFieldNames: Seq[String], outputFieldName: String, orderFieldName: String, orderedStringValues: Seq[String], criterionFieldName: String, criterionStringValue: String, predictAhead: Int, mlModelId: BSONObjectID, windowSize: Option[Int], reservoirNodeNum: ValueOrSeq[Int] = Left(None), reservoirInDegree: ValueOrSeq[Int] = Left(None), reservoirEdgesNum: ValueOrSeq[Int] = Left(None), reservoirPreferentialAttachment: Boolean = false, reservoirBias: Boolean = false, reservoirCircularInEdges: Option[Seq[Int]] = None, inputReservoirConnectivity: ValueOrSeq[Double] = Left(None), reservoirSpectralRadius: ValueOrSeq[Double] = Left(None), reservoirFunctionType: ActivationFunctionType, reservoirFunctionParams: Seq[Double] = Nil, washoutPeriod: ValueOrSeq[Int] = Left(None), learningSetting: RegressionLearningSetting, minCrossValidationTrainingSizeRatio: Option[Double], trainingTestSplitOrderValue: Option[Double])

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Value Members

  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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    @throws( ... )

  6. val criterionFieldName: String

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  7. val criterionStringValue: String

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  8. val dataSetId: String

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

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  10. def finalize(): Unit

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

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  12. val inputFieldNames: Seq[String]

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  13. val inputReservoirConnectivity: ValueOrSeq[Double]

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  14. final def isInstanceOf[T0]: Boolean

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  15. val learningSetting: RegressionLearningSetting

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  16. val minCrossValidationTrainingSizeRatio: Option[Double]

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  17. val mlModelId: BSONObjectID

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

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  19. final def notify(): Unit

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  20. final def notifyAll(): Unit

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  21. val orderFieldName: String

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  22. val orderedStringValues: Seq[String]

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  23. val outputFieldName: String

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  24. val predictAhead: Int

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  25. val reservoirBias: Boolean

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  26. val reservoirCircularInEdges: Option[Seq[Int]]

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  27. val reservoirEdgesNum: ValueOrSeq[Int]

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  28. val reservoirFunctionParams: Seq[Double]

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  29. val reservoirFunctionType: ActivationFunctionType

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  30. val reservoirInDegree: ValueOrSeq[Int]

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  31. val reservoirNodeNum: ValueOrSeq[Int]

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  32. val reservoirPreferentialAttachment: Boolean

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  33. def reservoirSpec: ReservoirSpec

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  34. val reservoirSpectralRadius: ValueOrSeq[Double]

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

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  36. val trainingTestSplitOrderValue: Option[Double]

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  37. final def wait(): Unit

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

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

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  40. val washoutPeriod: ValueOrSeq[Int]

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  41. val windowSize: Option[Int]

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