LogisticRegressionWithLBFGS

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. var addIntercept: Boolean

   Whether to add intercept (default: false).

   Whether to add intercept (default: false).

   Attributes

   protected

   Definition Classes

   GeneralizedLinearAlgorithm

7. final def asInstanceOf[T0]: T0

   Definition Classes

   Any

8. def clone(): AnyRef

   Attributes

   protected[java.lang]

   Definition Classes

   AnyRef

   Annotations

   @throws( ... )

9. def createModel(weights: Vector, intercept: Double): LogisticRegressionModel

   Create a model given the weights and intercept

   Create a model given the weights and intercept

   Attributes

   protected

   Definition Classes

   LogisticRegressionWithLBFGS → GeneralizedLinearAlgorithm

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

    Definition Classes

    AnyRef

11. def equals(arg0: Any): Boolean

    Definition Classes

    AnyRef → Any

12. def finalize(): Unit

    Attributes

    protected[java.lang]

    Definition Classes

    AnyRef

    Annotations

    @throws( classOf[java.lang.Throwable] )

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

    Definition Classes

    AnyRef → Any

14. def hashCode(): Int

    Definition Classes

    AnyRef → Any

15. final def isInstanceOf[T0]: Boolean

    Definition Classes

    Any

16. def isTraceEnabled(): Boolean

    Attributes

    protected

    Definition Classes

    Logging

17. def log: Logger

    Attributes

    protected

    Definition Classes

    Logging

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

    Attributes

    protected

    Definition Classes

    Logging

19. def logDebug(msg: ⇒ String): Unit

    Attributes

    protected

    Definition Classes

    Logging

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

    Attributes

    protected

    Definition Classes

    Logging

21. def logError(msg: ⇒ String): Unit

    Attributes

    protected

    Definition Classes

    Logging

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

    Attributes

    protected

    Definition Classes

    Logging

23. def logInfo(msg: ⇒ String): Unit

    Attributes

    protected

    Definition Classes

    Logging

24. def logName: String

    Attributes

    protected

    Definition Classes

    Logging

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

    Attributes

    protected

    Definition Classes

    Logging

26. def logTrace(msg: ⇒ String): Unit

    Attributes

    protected

    Definition Classes

    Logging

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

    Attributes

    protected

    Definition Classes

    Logging

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

    Attributes

    protected

    Definition Classes

    Logging

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

    Definition Classes

    AnyRef

30. final def notify(): Unit

    Definition Classes

    AnyRef

31. final def notifyAll(): Unit

    Definition Classes

    AnyRef

32. val optimizer: LBFGS

    The optimizer to solve the problem.

    The optimizer to solve the problem.

    Definition Classes

    LogisticRegressionWithLBFGS → GeneralizedLinearAlgorithm

33. def run(input: RDD[LabeledPoint], initialWeights: Vector): LogisticRegressionModel

    Run the algorithm with the configured parameters on an input RDD of LabeledPoint entries starting from the initial weights provided.

    Run the algorithm with the configured parameters on an input RDD of LabeledPoint entries starting from the initial weights provided.

    Definition Classes

    GeneralizedLinearAlgorithm

34. def run(input: RDD[LabeledPoint]): LogisticRegressionModel

    Run the algorithm with the configured parameters on an input RDD of LabeledPoint entries.

    Run the algorithm with the configured parameters on an input RDD of LabeledPoint entries.

    Definition Classes

    GeneralizedLinearAlgorithm

35. def setIntercept(addIntercept: Boolean): LogisticRegressionWithLBFGS.this.type

    Set if the algorithm should add an intercept.

    Set if the algorithm should add an intercept. Default false. We set the default to false because adding the intercept will cause memory allocation.

    Definition Classes

    GeneralizedLinearAlgorithm

36. def setValidateData(validateData: Boolean): LogisticRegressionWithLBFGS.this.type

    Set if the algorithm should validate data before training.

    Set if the algorithm should validate data before training. Default true.

    Definition Classes

    GeneralizedLinearAlgorithm

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

    Definition Classes

    AnyRef

38. def toString(): String

    Definition Classes

    AnyRef → Any

39. var validateData: Boolean

    Attributes

    protected

    Definition Classes

    GeneralizedLinearAlgorithm

40. val validators: List[(RDD[LabeledPoint]) ⇒ Boolean]

    Attributes

    protected

    Definition Classes

    LogisticRegressionWithLBFGS → GeneralizedLinearAlgorithm

41. final def wait(): Unit

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

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

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

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

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )