Packages

class TrainRegressor extends Estimator[TrainedRegressorModel] with AutoTrainer[TrainedRegressorModel] with SynapseMLLogging

Trains a regression model.

Linear Supertypes
SynapseMLLogging, AutoTrainer[TrainedRegressorModel], Wrappable, RWrappable, PythonWrappable, BaseWrappable, HasFeaturesCol, ComplexParamsWritable, MLWritable, HasInputCols, HasLabelCol, Estimator[TrainedRegressorModel], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. TrainRegressor
  2. SynapseMLLogging
  3. AutoTrainer
  4. Wrappable
  5. RWrappable
  6. PythonWrappable
  7. BaseWrappable
  8. HasFeaturesCol
  9. ComplexParamsWritable
  10. MLWritable
  11. HasInputCols
  12. HasLabelCol
  13. Estimator
  14. PipelineStage
  15. Logging
  16. Params
  17. Serializable
  18. Serializable
  19. Identifiable
  20. AnyRef
  21. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new TrainRegressor()
  2. new TrainRegressor(uid: String)

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. lazy val classNameHelper: String
    Attributes
    protected
    Definition Classes
    BaseWrappable
  7. final def clear(param: Param[_]): TrainRegressor.this.type
    Definition Classes
    Params
  8. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  9. def companionModelClassName: String
    Attributes
    protected
    Definition Classes
    BaseWrappable
  10. def copy(extra: ParamMap): Estimator[TrainedRegressorModel]
    Definition Classes
    TrainRegressor → Estimator → PipelineStage → Params
  11. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  12. lazy val copyrightLines: String
    Attributes
    protected
    Definition Classes
    BaseWrappable
  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. val featuresCol: Param[String]

    The name of the features column

    The name of the features column

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

    Fits the regression model.

    Fits the regression model.

    dataset

    The input dataset to train.

    returns

    The trained regression model.

    Definition Classes
    TrainRegressor → Estimator
  23. def fit(dataset: Dataset[_], paramMaps: Seq[ParamMap]): Seq[TrainedRegressorModel]
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  24. def fit(dataset: Dataset[_], paramMap: ParamMap): TrainedRegressorModel
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  25. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): TrainedRegressorModel
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" ) @varargs()
  26. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  27. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  28. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  29. def getFeaturesCol: String

    Definition Classes
    HasFeaturesCol
  30. def getInputCols: Array[String]

    Definition Classes
    HasInputCols
  31. def getLabelCol: String

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

    Definition Classes
    AutoTrainer
  33. def getNumFeatures: Int

    Definition Classes
    AutoTrainer
  34. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  35. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  36. def getParamInfo(p: Param[_]): ParamInfo[_]
    Definition Classes
    BaseWrappable
  37. def getPayload(methodName: String, numCols: Option[Int], executionSeconds: Option[Double], exception: Option[Exception]): Map[String, String]
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  38. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  39. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  40. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  41. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  42. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  43. val inputCols: StringArrayParam

    The names of the inputColumns

    The names of the inputColumns

    Definition Classes
    HasInputCols
  44. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  45. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  46. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  47. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  48. val labelCol: Param[String]

    The name of the label column

    The name of the label column

    Definition Classes
    HasLabelCol
  49. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  50. def logBase(info: Map[String, String], featureName: Option[String]): Unit
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  51. def logBase(methodName: String, numCols: Option[Int], executionSeconds: Option[Double], featureName: Option[String]): Unit
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  52. def logClass(featureName: String): Unit
    Definition Classes
    SynapseMLLogging
  53. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  54. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  55. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  56. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  57. def logErrorBase(methodName: String, e: Exception): Unit
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  58. def logFit[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  59. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  60. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  61. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  62. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  63. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  64. def logTransform[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  65. def logVerb[T](verb: String, f: ⇒ T, columns: Option[Int] = None): T
    Definition Classes
    SynapseMLLogging
  66. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  67. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  68. def makePyFile(conf: CodegenConfig): Unit
    Definition Classes
    PythonWrappable
  69. def makeRFile(conf: CodegenConfig): Unit
    Definition Classes
    RWrappable
  70. val model: EstimatorParam

    Model to run.

    Model to run. See doc on derived classes.

    Definition Classes
    AutoTrainer
  71. def modelDoc: String

    Doc for model to run.

    Doc for model to run.

    Definition Classes
    TrainRegressor → AutoTrainer
  72. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  73. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  74. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  75. val numFeatures: IntParam

    Number of features to hash to

    Number of features to hash to

    Definition Classes
    AutoTrainer
  76. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  77. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  78. lazy val pyClassDoc: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  79. lazy val pyClassName: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  80. def pyExtraEstimatorImports: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  81. def pyExtraEstimatorMethods: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  82. lazy val pyInheritedClasses: Seq[String]
    Attributes
    protected
    Definition Classes
    PythonWrappable
  83. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  84. lazy val pyInternalWrapper: Boolean
    Attributes
    protected
    Definition Classes
    PythonWrappable
  85. lazy val pyObjectBaseClass: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  86. def pyParamArg[T](p: Param[T]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  87. def pyParamDefault[T](p: Param[T]): Option[String]
    Attributes
    protected
    Definition Classes
    PythonWrappable
  88. def pyParamGetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  89. def pyParamSetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  90. def pyParamsArgs: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  91. def pyParamsDefaults: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  92. lazy val pyParamsDefinitions: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  93. def pyParamsGetters: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  94. def pyParamsSetters: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  95. def pythonClass(): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  96. def rClass(): String
    Attributes
    protected
    Definition Classes
    RWrappable
  97. def rDocString: String
    Attributes
    protected
    Definition Classes
    RWrappable
  98. def rExtraBodyLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  99. def rExtraInitLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  100. lazy val rFuncName: String
    Attributes
    protected
    Definition Classes
    RWrappable
  101. lazy val rInternalWrapper: Boolean
    Attributes
    protected
    Definition Classes
    RWrappable
  102. def rParamArg[T](p: Param[T]): String
    Attributes
    protected
    Definition Classes
    RWrappable
  103. def rParamsArgs: String
    Attributes
    protected
    Definition Classes
    RWrappable
  104. def rSetterLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  105. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  106. final def set(paramPair: ParamPair[_]): TrainRegressor.this.type
    Attributes
    protected
    Definition Classes
    Params
  107. final def set(param: String, value: Any): TrainRegressor.this.type
    Attributes
    protected
    Definition Classes
    Params
  108. final def set[T](param: Param[T], value: T): TrainRegressor.this.type
    Definition Classes
    Params
  109. final def setDefault(paramPairs: ParamPair[_]*): TrainRegressor.this.type
    Attributes
    protected
    Definition Classes
    Params
  110. final def setDefault[T](param: Param[T], value: T): TrainRegressor.this.type
    Attributes
    protected[org.apache.spark.ml]
    Definition Classes
    Params
  111. def setFeaturesCol(value: String): TrainRegressor.this.type

    Definition Classes
    HasFeaturesCol
  112. def setInputCols(value: Array[String]): TrainRegressor.this.type

    Definition Classes
    HasInputCols
  113. def setLabelCol(value: String): TrainRegressor.this.type

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

    Definition Classes
    AutoTrainer
  115. def setNumFeatures(value: Int): TrainRegressor.this.type

    Definition Classes
    AutoTrainer
  116. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  117. val thisStage: Params
    Attributes
    protected
    Definition Classes
    BaseWrappable
  118. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  119. def transformSchema(schema: StructType): StructType
    Definition Classes
    TrainRegressor → PipelineStage
    Annotations
    @DeveloperApi()
  120. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  121. val uid: String
    Definition Classes
    TrainRegressor → SynapseMLLogging → Identifiable
  122. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  123. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  124. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  125. def write: MLWriter
    Definition Classes
    ComplexParamsWritable → MLWritable

Inherited from SynapseMLLogging

Inherited from AutoTrainer[TrainedRegressorModel]

Inherited from Wrappable

Inherited from RWrappable

Inherited from PythonWrappable

Inherited from BaseWrappable

Inherited from HasFeaturesCol

Inherited from ComplexParamsWritable

Inherited from MLWritable

Inherited from HasInputCols

Inherited from HasLabelCol

Inherited from Estimator[TrainedRegressorModel]

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

getParam

param

setParam

Ungrouped