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 MMLParams with ComplexParamsWritable

Trains a regression model.

Linear Supertypes
ComplexParamsWritable, MMLParams, DefaultParamsWritable, 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. MMLParams
  4. DefaultParamsWritable
  5. MLWritable
  6. HasLabelCol
  7. Wrappable
  8. Estimator
  9. PipelineStage
  10. Logging
  11. Params
  12. Serializable
  13. Serializable
  14. Identifiable
  15. AnyRef
  16. Any
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Visibility
  1. Public
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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. def BooleanParam(i: Identifiable, name: String, description: String, default: Boolean): BooleanParam

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    Definition Classes
    Wrappable

  6. def BooleanParam(i: Identifiable, name: String, description: String): BooleanParam

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    Definition Classes
    Wrappable

  7. def DoubleParam(i: Identifiable, name: String, description: String, default: Double): DoubleParam

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    Definition Classes
    Wrappable

  8. def DoubleParam(i: Identifiable, name: String, description: String): DoubleParam

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    Definition Classes
    Wrappable

  9. def IntParam(i: Identifiable, name: String, description: String, validation: (Int) ⇒ Boolean): IntParam

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    Definition Classes
    Wrappable

  10. def IntParam(i: Identifiable, name: String, description: String, default: Int): IntParam

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    Definition Classes
    Wrappable

  11. def IntParam(i: Identifiable, name: String, description: String): IntParam

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    Definition Classes
    Wrappable

  12. def LongParam(i: Identifiable, name: String, description: String, default: Long): LongParam

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    Definition Classes
    Wrappable

  13. def LongParam(i: Identifiable, name: String, description: String): LongParam

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    Definition Classes
    Wrappable

  14. def StringParam(i: Identifiable, name: String, description: String, default: String, domain: Seq[String]): Param[String]

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    Definition Classes
    Wrappable

  15. def StringParam(i: Identifiable, name: String, description: String, default: String): Param[String]

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    Definition Classes
    Wrappable

  16. def StringParam(i: Identifiable, name: String, description: String, validation: (String) ⇒ Boolean): Param[String]

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    Definition Classes
    Wrappable

  17. def StringParam(i: Identifiable, name: String, description: String): Param[String]

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    Definition Classes
    Wrappable

  18. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  19. def chainedUid(origin: String): String

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    Definition Classes
    Wrappable

  20. final def clear(param: Param[_]): TrainRegressor.this.type

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    Definition Classes
    Params

  21. def clone(): AnyRef

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

  22. def copy(extra: ParamMap): Estimator[TrainedRegressorModel]

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    Definition Classes
    TrainRegressor → Estimator → PipelineStage → Params

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

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    Attributes
    protected
    Definition Classes
    Params

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

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    Attributes
    protected
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    Params

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

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    Definition Classes
    AnyRef

  26. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

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

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    Definition Classes
    Params

  28. def explainParams(): String

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    Definition Classes
    Params

  29. final def extractParamMap(): ParamMap

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    Definition Classes
    Params

  30. final def extractParamMap(extra: ParamMap): ParamMap

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    Definition Classes
    Params

  31. val featuresColumn: String

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  32. def finalize(): Unit

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

  33. 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

  34. def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[TrainedRegressorModel]

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )

  35. def fit(dataset: Dataset[_], paramMap: ParamMap): TrainedRegressorModel

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )

  36. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): TrainedRegressorModel

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" ) @varargs()

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

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    Definition Classes
    Params

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

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    Definition Classes
    AnyRef → Any

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

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    Definition Classes
    Params

  40. def getLabelCol: String

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    Definition Classes
    HasLabelCol

  41. def getModel: Estimator[_ <: Model[_]]

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  42. def getNumFeatures: Int

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

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    Definition Classes
    Params

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

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    Definition Classes
    Params

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

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    Definition Classes
    Params

  46. def hasParam(paramName: String): Boolean

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    Definition Classes
    Params

  47. def hashCode(): Int

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    Definition Classes
    AnyRef → Any

  48. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

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    Attributes
    protected
    Definition Classes
    Logging

  49. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Definition Classes
    Params

  51. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

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

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    Definition Classes
    Params

  53. def isTraceEnabled(): Boolean

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    Attributes
    protected
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    Logging

  54. val labelCol: Param[String]

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    The name of the label column

    The name of the label column

    Definition Classes
    HasLabelCol

  55. def log: Logger

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

  57. def logDebug(msg: ⇒ String): Unit

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    Attributes
    protected
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    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

  59. def logError(msg: ⇒ String): Unit

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    protected
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    Logging

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

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    Attributes
    protected
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    Logging

  61. def logInfo(msg: ⇒ String): Unit

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    Logging

  62. def logName: String

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    protected
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    Logging

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

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    Attributes
    protected
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    Logging

  64. def logTrace(msg: ⇒ String): Unit

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    Attributes
    protected
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    Logging

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

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    Attributes
    protected
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    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

  67. val model: EstimatorParam

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    Regressor to run

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

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    Definition Classes
    AnyRef

  69. final def notify(): Unit

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    Definition Classes
    AnyRef

  70. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

  71. val numFeatures: IntParam

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    Number of feature to hash to

  72. val paramDomains: Map[String, Seq[String]]

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    Definition Classes
    Wrappable

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

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    Definition Classes
    Params

  74. def save(path: String): Unit

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    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )

  75. final def set(paramPair: ParamPair[_]): TrainRegressor.this.type

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    Attributes
    protected
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    Params

  76. final def set(param: String, value: Any): TrainRegressor.this.type

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    Attributes
    protected
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    Params

  77. final def set[T](param: Param[T], value: T): TrainRegressor.this.type

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    Definition Classes
    Params

  78. final def setDefault(paramPairs: ParamPair[_]*): TrainRegressor.this.type

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    Attributes
    protected
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    Params

  79. final def setDefault[T](param: Param[T], value: T): TrainRegressor.this.type

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    Attributes
    protected
    Definition Classes
    Params

  80. def setLabelCol(value: String): TrainRegressor.this.type

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    Definition Classes
    HasLabelCol

  81. def setModel(value: Estimator[_ <: Model[_]]): TrainRegressor.this.type

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

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

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    Definition Classes
    AnyRef

  84. def toString(): String

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    Definition Classes
    Identifiable → AnyRef → Any

  85. def transformSchema(schema: StructType): StructType

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    Definition Classes
    TrainRegressor → PipelineStage
    Annotations
    @DeveloperApi()

  86. def transformSchema(schema: StructType, logging: Boolean): StructType

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    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()

  87. val uid: String

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    Definition Classes
    TrainRegressor → Identifiable

  88. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  91. def write: MLWriter

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    Definition Classes
    ComplexParamsWritable → MLWritable

Inherited from ComplexParamsWritable

Inherited from MMLParams

Inherited from DefaultParamsWritable

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