Packages

class TrainedRegressorModel extends AutoTrainedModel[TrainedRegressorModel] with Wrappable with SynapseMLLogging

Model produced by TrainRegressor.

Linear Supertypes
SynapseMLLogging, Wrappable, RWrappable, PythonWrappable, BaseWrappable, AutoTrainedModel[TrainedRegressorModel], HasFeaturesCol, HasLabelCol, ComplexParamsWritable, MLWritable, Model[TrainedRegressorModel], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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  2. By Inheritance
Inherited
  1. TrainedRegressorModel
  2. SynapseMLLogging
  3. Wrappable
  4. RWrappable
  5. PythonWrappable
  6. BaseWrappable
  7. AutoTrainedModel
  8. HasFeaturesCol
  9. HasLabelCol
  10. ComplexParamsWritable
  11. MLWritable
  12. Model
  13. Transformer
  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 TrainedRegressorModel()
  2. new TrainedRegressorModel(uid: String)

    uid

    The id of the module

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[_]): TrainedRegressorModel.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): TrainedRegressorModel
    Definition Classes
    TrainedRegressorModel → Model → Transformer → 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. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  23. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  24. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  25. def getFeaturesCol: String

    Definition Classes
    HasFeaturesCol
  26. def getLabelCol: String

    Definition Classes
    HasLabelCol
  27. def getLastStage: Transformer

    Retrieve the underlying model.

    Retrieve the underlying model.

    returns

    The underlying model.

    Definition Classes
    AutoTrainedModel
  28. def getModel: PipelineModel
    Definition Classes
    AutoTrainedModel
  29. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  30. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  31. def getParamInfo(p: Param[_]): ParamInfo[_]
    Definition Classes
    BaseWrappable
  32. def getParamMap: ParamMap

    Retrieve the param map from the underlying model.

    Retrieve the param map from the underlying model.

    returns

    The param map from the underlying model.

    Definition Classes
    AutoTrainedModel
  33. def getPayload(methodName: String, numCols: Option[Int], executionSeconds: Option[Double], exception: Option[Exception]): Map[String, String]
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  34. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  35. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  36. def hasParent: Boolean
    Definition Classes
    Model
  37. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  38. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  39. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  40. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  41. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  42. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  43. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  44. val labelCol: Param[String]

    The name of the label column

    The name of the label column

    Definition Classes
    HasLabelCol
  45. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  46. def logBase(info: Map[String, String], featureName: Option[String]): Unit
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  47. def logBase(methodName: String, numCols: Option[Int], executionSeconds: Option[Double], featureName: Option[String]): Unit
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  48. def logClass(featureName: String): Unit
    Definition Classes
    SynapseMLLogging
  49. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  50. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  51. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  52. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  53. def logErrorBase(methodName: String, e: Exception): Unit
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  54. def logFit[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  55. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  56. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  57. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  58. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  59. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  60. def logTransform[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  61. def logVerb[T](verb: String, f: ⇒ T, columns: Option[Int] = None): T
    Definition Classes
    SynapseMLLogging
  62. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  63. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  64. def makePyFile(conf: CodegenConfig): Unit
    Definition Classes
    PythonWrappable
  65. def makeRFile(conf: CodegenConfig): Unit
    Definition Classes
    RWrappable
  66. val model: TransformerParam
    Definition Classes
    AutoTrainedModel
  67. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  68. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  69. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  70. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  71. var parent: Estimator[TrainedRegressorModel]
    Definition Classes
    Model
  72. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  73. lazy val pyClassDoc: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  74. lazy val pyClassName: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  75. def pyExtraEstimatorImports: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  76. def pyExtraEstimatorMethods: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  77. lazy val pyInheritedClasses: Seq[String]
    Attributes
    protected
    Definition Classes
    PythonWrappable
  78. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  79. lazy val pyInternalWrapper: Boolean
    Attributes
    protected
    Definition Classes
    PythonWrappable
  80. lazy val pyObjectBaseClass: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  81. def pyParamArg[T](p: Param[T]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  82. def pyParamDefault[T](p: Param[T]): Option[String]
    Attributes
    protected
    Definition Classes
    PythonWrappable
  83. def pyParamGetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  84. def pyParamSetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  85. def pyParamsArgs: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  86. def pyParamsDefaults: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  87. lazy val pyParamsDefinitions: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  88. def pyParamsGetters: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  89. def pyParamsSetters: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  90. def pythonClass(): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  91. def rClass(): String
    Attributes
    protected
    Definition Classes
    RWrappable
  92. def rDocString: String
    Attributes
    protected
    Definition Classes
    RWrappable
  93. def rExtraBodyLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  94. def rExtraInitLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  95. lazy val rFuncName: String
    Attributes
    protected
    Definition Classes
    RWrappable
  96. lazy val rInternalWrapper: Boolean
    Attributes
    protected
    Definition Classes
    RWrappable
  97. def rParamArg[T](p: Param[T]): String
    Attributes
    protected
    Definition Classes
    RWrappable
  98. def rParamsArgs: String
    Attributes
    protected
    Definition Classes
    RWrappable
  99. def rSetterLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  100. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  101. final def set(paramPair: ParamPair[_]): TrainedRegressorModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  102. final def set(param: String, value: Any): TrainedRegressorModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  103. final def set[T](param: Param[T], value: T): TrainedRegressorModel.this.type
    Definition Classes
    Params
  104. final def setDefault(paramPairs: ParamPair[_]*): TrainedRegressorModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  105. final def setDefault[T](param: Param[T], value: T): TrainedRegressorModel.this.type
    Attributes
    protected[org.apache.spark.ml]
    Definition Classes
    Params
  106. def setFeaturesCol(value: String): TrainedRegressorModel.this.type

    Definition Classes
    HasFeaturesCol
  107. def setLabelCol(value: String): TrainedRegressorModel.this.type

    Definition Classes
    HasLabelCol
  108. def setModel(v: PipelineModel): TrainedRegressorModel.this.type
    Definition Classes
    AutoTrainedModel
  109. def setParent(parent: Estimator[TrainedRegressorModel]): TrainedRegressorModel
    Definition Classes
    Model
  110. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  111. val thisStage: Params
    Attributes
    protected
    Definition Classes
    BaseWrappable
  112. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  113. def transform(dataset: Dataset[_]): DataFrame
    Definition Classes
    TrainedRegressorModel → Transformer
  114. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  115. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  116. def transformSchema(schema: StructType): StructType
    Definition Classes
    TrainedRegressorModel → PipelineStage
    Annotations
    @DeveloperApi()
  117. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  118. val uid: String
    Definition Classes
    TrainedRegressorModel → SynapseMLLogging → Identifiable
  119. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  120. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  121. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  122. def write: MLWriter
    Definition Classes
    ComplexParamsWritable → MLWritable

Inherited from SynapseMLLogging

Inherited from Wrappable

Inherited from RWrappable

Inherited from PythonWrappable

Inherited from BaseWrappable

Inherited from AutoTrainedModel[TrainedRegressorModel]

Inherited from HasFeaturesCol

Inherited from HasLabelCol

Inherited from ComplexParamsWritable

Inherited from MLWritable

Inherited from Model[TrainedRegressorModel]

Inherited from Transformer

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