Class/Object

com.microsoft.ml.spark

TrainRegressor

Related Docs: object TrainRegressor | package spark

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class TrainRegressor extends Estimator[TrainedRegressorModel] with HasLabelCol with Wrappable with ComplexParamsWritable

Trains a regression model.

Linear Supertypes
ComplexParamsWritable, MLWritable, HasLabelCol, Wrappable, Estimator[TrainedRegressorModel], PipelineStage, org.apache.spark.internal.Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. TrainRegressor
  2. ComplexParamsWritable
  3. MLWritable
  4. HasLabelCol
  5. Wrappable
  6. Estimator
  7. PipelineStage
  8. Logging
  9. Params
  10. Serializable
  11. Serializable
  12. Identifiable
  13. AnyRef
  14. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new TrainRegressor()

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  2. new TrainRegressor(uid: String)

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Value Members

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

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    Definition Classes
    AnyRef → Any
  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any
  3. final def $[T](param: Param[T]): T

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    Attributes
    protected
    Definition Classes
    Params
  4. final def ==(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  5. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any
  6. final def clear(param: Param[_]): TrainRegressor.this.type

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    Definition Classes
    Params
  7. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  8. def copy(extra: ParamMap): Estimator[TrainedRegressorModel]

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    Definition Classes
    TrainRegressor → Estimator → PipelineStage → Params
  9. def copyValues[T <: Params](to: T, extra: ParamMap): T

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    Attributes
    protected
    Definition Classes
    Params
  10. final def defaultCopy[T <: Params](extra: ParamMap): T

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    Attributes
    protected
    Definition Classes
    Params
  11. final def eq(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef
  12. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  13. def explainParam(param: Param[_]): String

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    Definition Classes
    Params
  14. def explainParams(): String

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    Definition Classes
    Params
  15. final def extractParamMap(): ParamMap

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    Definition Classes
    Params
  16. final def extractParamMap(extra: ParamMap): ParamMap

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    Definition Classes
    Params
  17. val featuresColumn: String

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  18. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  19. def fit(dataset: Dataset[_]): TrainedRegressorModel

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    Fits the regression model.

    Fits the regression model.

    dataset

    The input dataset to train.

    returns

    The trained regression model.

    Definition Classes
    TrainRegressor → Estimator
  20. def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[TrainedRegressorModel]

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  21. def fit(dataset: Dataset[_], paramMap: ParamMap): TrainedRegressorModel

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  22. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): TrainedRegressorModel

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" ) @varargs()
  23. final def get[T](param: Param[T]): Option[T]

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    Definition Classes
    Params
  24. final def getClass(): Class[_]

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    Definition Classes
    AnyRef → Any
  25. final def getDefault[T](param: Param[T]): Option[T]

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    Definition Classes
    Params
  26. def getLabelCol: String

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    Definition Classes
    HasLabelCol
  27. def getModel: Estimator[_ <: Model[_]]

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  28. def getNumFeatures: Int

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

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    Definition Classes
    Params
  30. def getParam(paramName: String): Param[Any]

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    Definition Classes
    Params
  31. final def hasDefault[T](param: Param[T]): Boolean

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    Definition Classes
    Params
  32. def hasParam(paramName: String): Boolean

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    Definition Classes
    Params
  33. def hashCode(): Int

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    Definition Classes
    AnyRef → Any
  34. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

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    Attributes
    protected
    Definition Classes
    Logging
  35. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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    Attributes
    protected
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    Logging
  36. final def isDefined(param: Param[_]): Boolean

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    Definition Classes
    Params
  37. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any
  38. final def isSet(param: Param[_]): Boolean

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    Definition Classes
    Params
  39. def isTraceEnabled(): Boolean

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    Attributes
    protected
    Definition Classes
    Logging
  40. val labelCol: Param[String]

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    The name of the label column

    The name of the label column

    Definition Classes
    HasLabelCol
  41. def log: Logger

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    Attributes
    protected
    Definition Classes
    Logging
  42. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  43. def logDebug(msg: ⇒ String): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  44. def logError(msg: ⇒ String, throwable: Throwable): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  45. def logError(msg: ⇒ String): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  46. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  47. def logInfo(msg: ⇒ String): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  48. def logName: String

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    Attributes
    protected
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    Logging
  49. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

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    Attributes
    protected
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    Logging
  50. def logTrace(msg: ⇒ String): Unit

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    Attributes
    protected
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    Logging
  51. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

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    Attributes
    protected
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    Logging
  52. def logWarning(msg: ⇒ String): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  53. val model: EstimatorParam

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    Regressor to run

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

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    Definition Classes
    AnyRef
  55. final def notify(): Unit

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    Definition Classes
    AnyRef
  56. final def notifyAll(): Unit

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    Definition Classes
    AnyRef
  57. val numFeatures: IntParam

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    Number of feature to hash to

  58. lazy val params: Array[Param[_]]

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    Definition Classes
    Params
  59. def save(path: String): Unit

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    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  60. final def set(paramPair: ParamPair[_]): TrainRegressor.this.type

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    Attributes
    protected
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    Params
  61. final def set(param: String, value: Any): TrainRegressor.this.type

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    Attributes
    protected
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    Params
  62. final def set[T](param: Param[T], value: T): TrainRegressor.this.type

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    Definition Classes
    Params
  63. final def setDefault(paramPairs: ParamPair[_]*): TrainRegressor.this.type

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    Attributes
    protected
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    Params
  64. final def setDefault[T](param: Param[T], value: T): TrainRegressor.this.type

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    Attributes
    protected
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    Params
  65. def setLabelCol(value: String): TrainRegressor.this.type

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    Definition Classes
    HasLabelCol
  66. def setModel(value: Estimator[_ <: Model[_]]): TrainRegressor.this.type

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  67. def setNumFeatures(value: Int): TrainRegressor.this.type

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

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    Definition Classes
    AnyRef
  69. def toString(): String

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    Definition Classes
    Identifiable → AnyRef → Any
  70. def transformSchema(schema: StructType): StructType

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    Definition Classes
    TrainRegressor → PipelineStage
    Annotations
    @DeveloperApi()
  71. def transformSchema(schema: StructType, logging: Boolean): StructType

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    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  72. val uid: String

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    Definition Classes
    TrainRegressor → Identifiable
  73. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  74. final def wait(arg0: Long, arg1: Int): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  75. final def wait(arg0: Long): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  76. def write: MLWriter

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    Definition Classes
    ComplexParamsWritable → MLWritable

Inherited from ComplexParamsWritable

Inherited from MLWritable

Inherited from HasLabelCol

Inherited from Wrappable

Inherited from Estimator[TrainedRegressorModel]

Inherited from PipelineStage

Inherited from org.apache.spark.internal.Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

Parameters

A list of parameter keys this algorithm can take. Users can set and get the parameter values through setters and getters

Parameter setters

Parameter getters

Members