edu.cmu.ml.rtw.pra.models

SgdLogisticRegressionModel

class SgdLogisticRegressionModel[T <: Instance] extends OnlineModel

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OnlineModel, AnyRef, Any
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  1. SgdLogisticRegressionModel
  2. OnlineModel
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Instance Constructors

  1. new SgdLogisticRegressionModel(params: JValue, outputter: Outputter)

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. val _iterations: Int

  7. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  8. def classifyInstance(instance: MatrixRow): Double

    Definition Classes
    SgdLogisticRegressionModel → OnlineModel

  9. def clone(): AnyRef

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

  10. def computeLambda(): Double

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

    Definition Classes
    AnyRef

  12. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  13. def finalize(): Unit

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

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

    Definition Classes
    AnyRef → Any

  15. def getWeights(): WrappedArray[Double]

    Definition Classes
    SgdLogisticRegressionModel → OnlineModel

  16. def growFeatures(newSize: Int): Unit

  17. def hashCode(): Int

    Definition Classes
    AnyRef → Any

  18. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  19. var iteration: Int

  20. def iterations(): Int

    Definition Classes
    SgdLogisticRegressionModel → OnlineModel

  21. var k: Int

  22. val l2Weight: Double

  23. var lastUpdated: Array[Int]

  24. val learningRateA: Double

  25. val learningRateB: Double

  26. val learningRateMomentum: Double

  27. var logConditionalLikelihood: Double

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

    Definition Classes
    AnyRef

  29. def nextIteration(): Unit

    Definition Classes
    SgdLogisticRegressionModel → OnlineModel

  30. final def notify(): Unit

    Definition Classes
    AnyRef

  31. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  32. var numFeatures: Int

  33. val overflow: Int

  34. val paramKeys: Seq[String]

  35. def sigmoid(x: Double): Double

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

    Definition Classes
    AnyRef

  37. def toString(): String

    Definition Classes
    AnyRef → Any

  38. def updateWeights(instance: MatrixRow): Unit

    Definition Classes
    SgdLogisticRegressionModel → OnlineModel

  39. var velocity: Array[Double]

  40. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  43. var weights: Array[Double]

Inherited from OnlineModel

Inherited from AnyRef

Inherited from Any

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