com.github.cloudml.zen.ml.recommendation

BSFMRegression

class BSFMRegression extends BSFM

Linear Supertypes
BSFM, Logging, Serializable, Serializable, AnyRef, Any
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Inherited
  1. BSFMRegression
  2. BSFM
  3. Logging
  4. Serializable
  5. Serializable
  6. AnyRef
  7. Any
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Instance Constructors

  1. new BSFMRegression(input: RDD[(VertexId, LabeledPoint)], stepSize: Double = 1e-2, views: Array[Long], l2Reg: (Double, Double, Double) = (1e-3, 1e-3, 1e-3), rank: Int = 20, useAdaGrad: Boolean = true, miniBatchFraction: Double = 1.0, storageLevel: StorageLevel = StorageLevel.MEMORY_AND_DISK)

  2. new BSFMRegression(_dataSet: Graph[VD, ED], stepSize: Double, views: Array[Long], l2: (Double, Double, Double), rank: Int, useAdaGrad: Boolean, miniBatchFraction: Double, storageLevel: StorageLevel)

Value Members

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

    Definition Classes
    AnyRef

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

    Definition Classes
    Any

  3. final def ##(): Int

    Definition Classes
    AnyRef → Any

  4. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

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

    Definition Classes
    Any

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

    Attributes
    protected
    Definition Classes
    BSFM

  7. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  8. def backward(q: VertexRDD[VD], iter: Int): (Double, VertexRDD[Array[Double]])

    Attributes
    protected
    Definition Classes
    BSFM

  9. var bias: Double

    Attributes
    protected
    Definition Classes
    BSFM

  10. def checkpointGradientSum(): Unit

    Attributes
    protected
    Definition Classes
    BSFM

  11. val checkpointInterval: Int

    Attributes
    protected
    Definition Classes
    BSFM

  12. def checkpointVertices(): Unit

    Attributes
    protected
    Definition Classes
    BSFM

  13. def clone(): AnyRef

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

  14. var dataSet: Graph[VD, ED]

    Attributes
    protected
    Definition Classes
    BSFM

  15. var edges: EdgeRDD[ED]

    Attributes
    protected
    Definition Classes
    BSFM

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

    Definition Classes
    AnyRef

  17. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

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

    Attributes
    protected
    Definition Classes
    BSFM

  19. def features: VertexRDD[VD]

    Definition Classes
    BSFM

  20. def finalize(): Unit

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

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

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

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

    Definition Classes
    AnyRef → Any

  23. var gradientSum: (Double, VertexRDD[Array[Double]])

    Attributes
    protected
    Definition Classes
    BSFM

  24. def hashCode(): Int

    Definition Classes
    AnyRef → Any

  25. def intercept: Double

    Definition Classes
    BSFM

  26. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  27. def isTraceEnabled(): Boolean

    Attributes
    protected
    Definition Classes
    Logging

  28. val l2: (Double, Double, Double)

    Definition Classes
    BSFMRegression → BSFM

  29. def log: Logger

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

  36. def logName: String

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

  41. def loss(q: VertexRDD[VD]): Double

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

  42. def mask: Int

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

  43. val miniBatchFraction: Double

    Definition Classes
    BSFMRegression → BSFM

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

    Attributes
    protected
    Definition Classes
    BSFM

  45. def multiplier(q: VertexRDD[VD]): VertexRDD[VD]

    Attributes
    protected
    Definition Classes
    BSFMRegression → BSFM

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

    Definition Classes
    AnyRef

  47. final def notify(): Unit

    Definition Classes
    AnyRef

  48. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  49. var numFeatures: Long

    Attributes
    protected
    Definition Classes
    BSFM

  50. var numSamples: Long

    Attributes
    protected
    Definition Classes
    BSFM

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

    Attributes
    protected
    Definition Classes
    BSFMRegression → BSFM

  52. val rank: Int

    Definition Classes
    BSFMRegression → BSFM

  53. def run(iterations: Int): Unit

    Definition Classes
    BSFM

  54. def samples: VertexRDD[VD]

    Definition Classes
    BSFM

  55. def saveModel(): BSFMModel

    Definition Classes
    BSFM

  56. def setDataSet(data: Graph[VD, ED]): BSFMRegression.this.type

    Definition Classes
    BSFM

  57. val stepSize: Double

    Definition Classes
    BSFMRegression → BSFM

  58. val storageLevel: StorageLevel

    Definition Classes
    BSFMRegression → BSFM

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

    Definition Classes
    AnyRef

  60. def toString(): String

    Definition Classes
    AnyRef → Any

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

    Attributes
    protected
    Definition Classes
    BSFM

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

    Attributes
    protected
    Definition Classes
    BSFM

  63. val useAdaGrad: Boolean

    Definition Classes
    BSFMRegression → BSFM

  64. var vertices: VertexRDD[VD]

    Attributes
    protected
    Definition Classes
    BSFM

  65. val views: Array[Long]

    Definition Classes
    BSFMRegression → BSFM

  66. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from BSFM

Inherited from Logging

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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