ml.dmlc.xgboost4j.scala.spark.params

# GeneralParams

###
Related Doc: package params

#### trait GeneralParams extends Params

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Params, Serializable, Serializable, Identifiable, AnyRef, Any
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XGBoostEstimator
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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 checkpointInterval: IntParam

   Param for set checkpoint interval (>= 1) or disable checkpoint (-1).

   Param for set checkpoint interval (>= 1) or disable checkpoint (-1). E.g. 10 means that the trained model will get checkpointed every 10 iterations. Note: `checkpoint_path` must also be set if the checkpoint interval is greater than 0.

7. #### val checkpointPath: Param[String]

   The hdfs folder to load and save checkpoint boosters.

   The hdfs folder to load and save checkpoint boosters. default: `empty_string`

8. #### final def clear(param: Param[_]): GeneralParams.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. #### val customEval: CustomEvalParam

    customized evaluation function provided by user.

    customized evaluation function provided by user. default: null

12. #### val customObj: CustomObjParam

    customized objective function provided by user.

    customized objective function provided by user. default: null

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

    Attributes
      protected
    Definition Classes
      Params

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

    Definition Classes
      AnyRef

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

    Definition Classes
      AnyRef → Any

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

    Definition Classes
      Params

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

    Definition Classes
      Params

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

    Definition Classes
      Params

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

    Definition Classes
      Params

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

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

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

    Definition Classes
      Params

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

    Definition Classes
      AnyRef → Any

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

    Definition Classes
      Params

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

    Definition Classes
      Params

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

    Definition Classes
      Params

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. #### val missing: FloatParam

    the value treated as missing.

    the value treated as missing. default: Float.NaN

33. #### val nWorkers: IntParam

    number of workers used to train xgboost model.

    number of workers used to train xgboost model. default: 1

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

    Definition Classes
      AnyRef

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

    Definition Classes
      AnyRef

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

    Definition Classes
      AnyRef

37. #### val numThreadPerTask: IntParam

    number of threads used by per worker.

    number of threads used by per worker. default 1

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

    Definition Classes
      Params

39. #### val round: IntParam

    The number of rounds for boosting

40. #### val seed: LongParam

    Random seed for the C++ part of XGBoost and train/test splitting.

41. #### final def set(paramPair: ParamPair[_]): GeneralParams.this.type

    Attributes
      protected
    Definition Classes
      Params

42. #### final def set(param: String, value: Any): GeneralParams.this.type

    Attributes
      protected
    Definition Classes
      Params

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

    Definition Classes
      Params

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

    Attributes
      protected
    Definition Classes
      Params

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

    Attributes
      protected
    Definition Classes
      Params

46. #### val silent: IntParam

    0 means printing running messages, 1 means silent mode.

    0 means printing running messages, 1 means silent mode. default: 0

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

    Definition Classes
      AnyRef

48. #### val timeoutRequestWorkers: LongParam

    the maximum time to wait for the job requesting new workers.

    the maximum time to wait for the job requesting new workers. default: 30 minutes

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

    Definition Classes
      Identifiable → AnyRef → Any

50. #### val trackerConf: TrackerConfParam

    Rabit tracker configurations.

    Rabit tracker configurations. The parameter must be provided as an instance of the TrackerConf class, which has the following definition:

    case class TrackerConf(workerConnectionTimeout: Duration, trainingTimeout: Duration, trackerImpl: String)

    See below for detailed explanations.

    - trackerImpl: Select the implementation of Rabit tracker. default: "python"

    Choice between "python" or "scala". The former utilizes the Java wrapper of the Python Rabit tracker (in dmlc_core), and does not support timeout settings. The "scala" version removes Python components, and fully supports timeout settings.

    - workerConnectionTimeout: the maximum wait time for all workers to connect to the tracker. default: 0 millisecond (no timeout)

    The timeout value should take the time of data loading and pre-processing into account, due to the lazy execution of Spark's operations. Alternatively, you may force Spark to perform data transformation before calling XGBoost.train(), so that this timeout truly reflects the connection delay. Set a reasonable timeout value to prevent model training/testing from hanging indefinitely, possible due to network issues. Note that zero timeout value means to wait indefinitely (equivalent to Duration.Inf). Ignored if the tracker implementation is "python".

51. #### val useExternalMemory: BooleanParam

    whether to use external memory as cache.

    whether to use external memory as cache. default: false

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

    Definition Classes
      AnyRef
    Annotations
      @throws( ... )

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

    Definition Classes
      AnyRef
    Annotations
      @throws( ... )

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

    Definition Classes
      AnyRef
    Annotations
      @throws( ... )

### Inherited from Params

### Inherited from Serializable

### Inherited from Identifiable

### Inherited from AnyRef

### Inherited from Any

### Ungrouped