Class

com.github.cloudml.zen.ml.recommendation

MVMRegression

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class MVMRegression extends MVM

Linear Supertypes
MVM, Logging, Serializable, Serializable, AnyRef, Any
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Inherited
  1. MVMRegression
  2. MVM
  3. Logging
  4. Serializable
  5. Serializable
  6. AnyRef
  7. Any
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Visibility
  1. Public
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Instance Constructors

  1. new MVMRegression(input: RDD[(VertexId, LabeledPoint)], stepSize: Double = 1e-2, views: Array[Long], regParam: Double = 1e-2, elasticNetParam: Double = 0, rank: Int = 20, useAdaGrad: Boolean = true, useWeightedLambda: Boolean = true, miniBatchFraction: Double = 1.0, storageLevel: StorageLevel = StorageLevel.MEMORY_AND_DISK)

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  2. new MVMRegression(_dataSet: Graph[VD, ED], stepSize: Double, views: Array[Long], regParam: Double, elasticNetParam: Double, rank: Int, useAdaGrad: Boolean, useWeightedLambda: Boolean, miniBatchFraction: Double, storageLevel: StorageLevel)

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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. def adaGrad(gradientSum: VertexRDD[Array[Double]], gradient: VertexRDD[Array[Double]], epsilon: Double, rho: Double, iter: Int): VertexRDD[(Array[Double], Array[Double])]

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    Attributes
    protected
    Definition Classes
    MVM

  5. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  6. def backward(q: VertexRDD[VD], iter: Int): (Long, Double, VertexRDD[VD])

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    Attributes
    protected
    Definition Classes
    MVM

  7. def checkpointGradientSum(delta: VertexRDD[(Array[Double], Array[Double])]): Unit

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    Attributes
    protected
    Definition Classes
    MVM

  8. val checkpointInterval: Int

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    Attributes
    protected
    Definition Classes
    MVM

  9. def checkpointVertices(): Unit

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    Attributes
    protected
    Definition Classes
    MVM

  10. def clone(): AnyRef

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

  11. var dataSet: Graph[VD, ED]

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    Attributes
    protected
    Definition Classes
    MVM

  12. var edges: EdgeRDD[ED]

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    Attributes
    protected
    Definition Classes
    MVM

  13. val elasticNetParam: Double

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    Definition Classes
    MVMRegression → MVM

  14. def epsilon: Double

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    Definition Classes
    MVM

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

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    Definition Classes
    AnyRef

  16. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  17. def esgd(gradientSum: VertexRDD[Array[Double]], gradient: VertexRDD[Array[Double]], epsilon: Double, rho: Double, iter: Int): VertexRDD[(Array[Double], Array[Double])]

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    Attributes
    protected
    Definition Classes
    MVM

  18. def features: VertexRDD[VD]

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    Definition Classes
    MVM

  19. def finalize(): Unit

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

  20. def forward(iter: Int): VertexRDD[Array[Double]]

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    Attributes
    protected[com.github.cloudml.zen.ml]
    Definition Classes
    MVM

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

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    Definition Classes
    AnyRef → Any

  22. var gradientSum: VertexRDD[Array[Double]]

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    Attributes
    protected
    Definition Classes
    MVM

  23. def halfLife: Int

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    Definition Classes
    MVM

  24. def hashCode(): Int

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    Definition Classes
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  25. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

  26. def isTraceEnabled(): Boolean

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    Attributes
    protected
    Definition Classes
    Logging

  27. def log: Logger

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    Attributes
    protected
    Definition Classes
    Logging

  28. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

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    Attributes
    protected
    Definition Classes
    Logging

  29. def logDebug(msg: ⇒ String): Unit

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    Attributes
    protected
    Definition Classes
    Logging

  30. def logError(msg: ⇒ String, throwable: Throwable): Unit

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    Attributes
    protected
    Definition Classes
    Logging

  31. def logError(msg: ⇒ String): Unit

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    protected
    Definition Classes
    Logging

  32. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

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    Attributes
    protected
    Definition Classes
    Logging

  33. def logInfo(msg: ⇒ String): Unit

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    Attributes
    protected
    Definition Classes
    Logging

  34. def logName: String

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

  36. def logTrace(msg: ⇒ String): Unit

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

  38. def logWarning(msg: ⇒ String): Unit

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    Attributes
    protected
    Definition Classes
    Logging

  39. def mask: Int

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    Attributes
    protected[com.github.cloudml.zen.ml]
    Definition Classes
    MVM

  40. val miniBatchFraction: Double

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    Definition Classes
    MVMRegression → MVM

  41. var multi: VertexRDD[Array[Double]]

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    Attributes
    protected
    Definition Classes
    MVM

  42. def multiplier(q: VertexRDD[VD], iter: Int): (Long, Double, VertexRDD[VD])

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    Attributes
    protected
    Definition Classes
    MVMRegression → MVM

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

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    Definition Classes
    AnyRef

  44. final def notify(): Unit

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    Definition Classes
    AnyRef

  45. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

  46. var numFeatures: Long

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    Attributes
    protected
    Definition Classes
    MVM

  47. var numSamples: Long

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    Attributes
    protected
    Definition Classes
    MVM

  48. def predict(arr: Array[Double]): Double

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    Attributes
    protected
    Definition Classes
    MVMRegression → MVM

  49. val rank: Int

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    Definition Classes
    MVMRegression → MVM

  50. val regParam: Double

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    Definition Classes
    MVMRegression → MVM

  51. def run(iterations: Int): Unit

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    Definition Classes
    MVM

  52. def samples: VertexRDD[VD]

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    Definition Classes
    MVM

  53. def saveModel(): MVMModel

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    Definition Classes
    MVM

  54. def setDataSet(data: Graph[VD, ED]): MVMRegression.this.type

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    Definition Classes
    MVM

  55. val stepSize: Double

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    Definition Classes
    MVMRegression → MVM

  56. val storageLevel: StorageLevel

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    Definition Classes
    MVMRegression → MVM

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

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    Definition Classes
    AnyRef

  58. def toString(): String

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    Definition Classes
    AnyRef → Any

  59. def updateGradientSum(gradient: VertexRDD[Array[Double]], iter: Int): VertexRDD[Array[Double]]

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    Attributes
    protected
    Definition Classes
    MVM

  60. def updateWeight(delta: VertexRDD[Array[Double]], iter: Int): VertexRDD[VD]

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    Attributes
    protected
    Definition Classes
    MVM

  61. val useAdaGrad: Boolean

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    Definition Classes
    MVMRegression → MVM

  62. val useWeightedLambda: Boolean

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    Definition Classes
    MVMRegression → MVM

  63. var vertices: VertexRDD[VD]

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    Attributes
    protected
    Definition Classes
    MVM

  64. val views: Array[Long]

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    Definition Classes
    MVMRegression → MVM

  65. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from MVM

Inherited from Logging

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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