ml.dmlc.xgboost4j.scala.spark.params

# LearningTaskParams

###
Related Doc: package params

#### trait LearningTaskParams extends Params

Linear Supertypes
Params, Serializable, Serializable, Identifiable, AnyRef, Any
Known Subclasses
XGBoostEstimator
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1. LearningTaskParams
2. Params
3. Serializable
4. Serializable
5. Identifiable
6. AnyRef
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### Abstract Value Members

1. #### abstract def copy(extra: ParamMap): Params

   Definition Classes
     Params

2. #### abstract val uid: String

   Definition Classes
     Identifiable

### Concrete Value Members

1. #### final def !=(arg0: Any): Boolean

   Definition Classes
     AnyRef → Any

2. #### final def ##(): Int

   Definition Classes
     AnyRef → Any

3. #### final def $[T](param: Param[T]): T

   Attributes
     protected
   Definition Classes
     Params

4. #### final def ==(arg0: Any): Boolean

   Definition Classes
     AnyRef → Any

5. #### final def asInstanceOf[T0]: T0

   Definition Classes
     Any

6. #### val baseMarginCol: Param[String]

   Initial prediction (aka base margin) column name.

7. #### val baseScore: DoubleParam

   the initial prediction score of all instances, global bias.

   the initial prediction score of all instances, global bias. default=0.5

8. #### final def clear(param: Param[_]): LearningTaskParams.this.type

   Definition Classes
     Params

9. #### def clone(): AnyRef

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

10. #### def copyValues[T <: Params](to: T, extra: ParamMap): T

    Attributes
      protected
    Definition Classes
      Params

11. #### final def defaultCopy[T <: Params](extra: ParamMap): T

    Attributes
      protected
    Definition Classes
      Params

12. #### final def eq(arg0: AnyRef): Boolean

    Definition Classes
      AnyRef

13. #### def equals(arg0: Any): Boolean

    Definition Classes
      AnyRef → Any

14. #### val evalMetric: Param[String]

    evaluation metrics for validation data, a default metric will be assigned according to objective(rmse for regression, and error for classification, mean average precision for ranking).

    evaluation metrics for validation data, a default metric will be assigned according to objective(rmse for regression, and error for classification, mean average precision for ranking). options: rmse, mae, logloss, error, merror, mlogloss, auc, aucpr, ndcg, map, gamma-deviance

15. #### def explainParam(param: Param[_]): String

    Definition Classes
      Params

16. #### def explainParams(): String

    Definition Classes
      Params

17. #### final def extractParamMap(): ParamMap

    Definition Classes
      Params

18. #### final def extractParamMap(extra: ParamMap): ParamMap

    Definition Classes
      Params

19. #### def finalize(): Unit

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

20. #### final def get[T](param: Param[T]): Option[T]

    Definition Classes
      Params

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

    Definition Classes
      AnyRef → Any

22. #### final def getDefault[T](param: Param[T]): Option[T]

    Definition Classes
      Params

23. #### final def getOrDefault[T](param: Param[T]): T

    Definition Classes
      Params

24. #### def getParam(paramName: String): Param[Any]

    Definition Classes
      Params

25. #### val groupData: GroupDataParam

    group data specify each group sizes for ranking task.

    group data specify each group sizes for ranking task. To correspond to partition of training data, it is nested.

26. #### final def hasDefault[T](param: Param[T]): Boolean

    Definition Classes
      Params

27. #### def hasParam(paramName: String): Boolean

    Definition Classes
      Params

28. #### def hashCode(): Int

    Definition Classes
      AnyRef → Any

29. #### final def isDefined(param: Param[_]): Boolean

    Definition Classes
      Params

30. #### final def isInstanceOf[T0]: Boolean

    Definition Classes
      Any

31. #### final def isSet(param: Param[_]): Boolean

    Definition Classes
      Params

32. #### final def ne(arg0: AnyRef): Boolean

    Definition Classes
      AnyRef

33. #### final def notify(): Unit

    Definition Classes
      AnyRef

34. #### final def notifyAll(): Unit

    Definition Classes
      AnyRef

35. #### val numClasses: IntParam

    number of tasks to learn

36. #### val numEarlyStoppingRounds: IntParam

    If non-zero, the training will be stopped after a specified number of consecutive increases in any evaluation metric.

37. #### val objective: Param[String]

    Specify the learning task and the corresponding learning objective.

    Specify the learning task and the corresponding learning objective. options: reg:linear, reg:logistic, binary:logistic, binary:logitraw, count:poisson, multi:softmax, multi:softprob, rank:pairwise, reg:gamma. default: reg:linear

38. #### lazy val params: Array[Param[_]]

    Definition Classes
      Params

39. #### final def set(paramPair: ParamPair[_]): LearningTaskParams.this.type

    Attributes
      protected
    Definition Classes
      Params

40. #### final def set(param: String, value: Any): LearningTaskParams.this.type

    Attributes
      protected
    Definition Classes
      Params

41. #### final def set[T](param: Param[T], value: T): LearningTaskParams.this.type

    Definition Classes
      Params

42. #### final def setDefault(paramPairs: ParamPair[_]*): LearningTaskParams.this.type

    Attributes
      protected
    Definition Classes
      Params

43. #### final def setDefault[T](param: Param[T], value: T): LearningTaskParams.this.type

    Attributes
      protected
    Definition Classes
      Params

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

    Definition Classes
      AnyRef

45. #### def toString(): String

    Definition Classes
      Identifiable → AnyRef → Any

46. #### val trainTestRatio: DoubleParam

    Fraction of training points to use for testing.

47. #### final def wait(): Unit

    Definition Classes
      AnyRef
    Annotations
      @throws( ... )

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

    Definition Classes
      AnyRef
    Annotations
      @throws( ... )

49. #### final def wait(arg0: Long): Unit

    Definition Classes
      AnyRef
    Annotations
      @throws( ... )

50. #### val weightCol: Param[String]

    Instance weights column name.

### Inherited from Params

### Inherited from Serializable

### Inherited from Identifiable

### Inherited from AnyRef

### Inherited from Any

### Ungrouped