Packages

class DummyRegressor extends Regressor[Vector, DummyRegressor, DummyRegressionModel] with DummyRegressorParams with DefaultParamsWritable

Source
DummyRegressor.scala
Linear Supertypes
DefaultParamsWritable, MLWritable, DummyRegressorParams, HasTol, Regressor[Vector, DummyRegressor, DummyRegressionModel], Predictor[Vector, DummyRegressor, DummyRegressionModel], PredictorParams, HasPredictionCol, HasFeaturesCol, HasLabelCol, Estimator[DummyRegressionModel], PipelineStage, Logging, Params, Serializable, Identifiable, AnyRef, Any
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  2. Alphabetic
  3. By Inheritance
Inherited
  1. DummyRegressor
  2. DefaultParamsWritable
  3. MLWritable
  4. DummyRegressorParams
  5. HasTol
  6. Regressor
  7. Predictor
  8. PredictorParams
  9. HasPredictionCol
  10. HasFeaturesCol
  11. HasLabelCol
  12. Estimator
  13. PipelineStage
  14. Logging
  15. Params
  16. Serializable
  17. Identifiable
  18. AnyRef
  19. Any
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Visibility
  1. Public
  2. Protected

Instance Constructors

  1. new DummyRegressor()
  2. new DummyRegressor(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. final def clear(param: Param[_]): DummyRegressor.this.type
    Definition Classes
    Params
  7. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.CloneNotSupportedException]) @native()
  8. val constant: Param[Double]

    param for the constant predicted by the predictor

    param for the constant predicted by the predictor

    Definition Classes
    DummyRegressorParams
  9. def copy(extra: ParamMap): DummyRegressor
    Definition Classes
    DummyRegressor → Predictor → Estimator → PipelineStage → Params
  10. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  11. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  12. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  13. def equals(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef → Any
  14. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  15. def explainParams(): String
    Definition Classes
    Params
  16. def extractInstances(dataset: Dataset[_], validateInstance: (Instance) => Unit): RDD[Instance]
    Attributes
    protected
    Definition Classes
    PredictorParams
  17. def extractInstances(dataset: Dataset[_]): RDD[Instance]
    Attributes
    protected
    Definition Classes
    PredictorParams
  18. def extractLabeledPoints(dataset: Dataset[_]): RDD[LabeledPoint]
    Attributes
    protected
    Definition Classes
    Predictor
  19. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  20. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  21. final val featuresCol: Param[String]
    Definition Classes
    HasFeaturesCol
  22. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.Throwable])
  23. def fit(dataset: Dataset[_]): DummyRegressionModel
    Definition Classes
    Predictor → Estimator
  24. def fit(dataset: Dataset[_], paramMaps: Seq[ParamMap]): Seq[DummyRegressionModel]
    Definition Classes
    Estimator
    Annotations
    @Since("2.0.0")
  25. def fit(dataset: Dataset[_], paramMap: ParamMap): DummyRegressionModel
    Definition Classes
    Estimator
    Annotations
    @Since("2.0.0")
  26. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DummyRegressionModel
    Definition Classes
    Estimator
    Annotations
    @Since("2.0.0") @varargs()
  27. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  28. final def getClass(): Class[_ <: AnyRef]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  29. def getConstant: Double

    Definition Classes
    DummyRegressorParams
  30. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  31. final def getFeaturesCol: String
    Definition Classes
    HasFeaturesCol
  32. final def getLabelCol: String
    Definition Classes
    HasLabelCol
  33. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  34. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  35. final def getPredictionCol: String
    Definition Classes
    HasPredictionCol
  36. def getQuantile: Double

    Definition Classes
    DummyRegressorParams
  37. def getStrategy: String
    Definition Classes
    DummyRegressorParams
  38. final def getTol: Double
    Definition Classes
    HasTol
  39. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  40. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  41. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  42. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  43. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  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. final val labelCol: Param[String]
    Definition Classes
    HasLabelCol
  49. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  50. def logDebug(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  51. def logDebug(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  52. def logError(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  53. def logError(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  54. def logInfo(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  55. def logInfo(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  56. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  57. def logTrace(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  58. def logTrace(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  59. def logWarning(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  60. def logWarning(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  61. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  62. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  63. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  64. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  65. final val predictionCol: Param[String]
    Definition Classes
    HasPredictionCol
  66. val quantile: Param[Double]

    param for the quantile estimated predicted by the predictor when strategy='quantile'

    param for the quantile estimated predicted by the predictor when strategy='quantile'

    Definition Classes
    DummyRegressorParams
  67. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since("1.6.0") @throws("If the input path already exists but overwrite is not enabled.")
  68. final def set(paramPair: ParamPair[_]): DummyRegressor.this.type
    Attributes
    protected
    Definition Classes
    Params
  69. final def set(param: String, value: Any): DummyRegressor.this.type
    Attributes
    protected
    Definition Classes
    Params
  70. final def set[T](param: Param[T], value: T): DummyRegressor.this.type
    Definition Classes
    Params
  71. def setConstant(value: Double): DummyRegressor.this.type

  72. final def setDefault(paramPairs: ParamPair[_]*): DummyRegressor.this.type
    Attributes
    protected
    Definition Classes
    Params
  73. final def setDefault[T](param: Param[T], value: T): DummyRegressor.this.type
    Attributes
    protected
    Definition Classes
    Params
  74. def setFeaturesCol(value: String): DummyRegressor
    Definition Classes
    Predictor
  75. def setLabelCol(value: String): DummyRegressor
    Definition Classes
    Predictor
  76. def setPredictionCol(value: String): DummyRegressor
    Definition Classes
    Predictor
  77. def setQuantile(value: Double): DummyRegressor.this.type

  78. def setStrategy(value: String): DummyRegressor.this.type

  79. def setTol(value: Double): DummyRegressor.this.type

  80. val strategy: Param[String]

    strategy to use to generate predictions.

    strategy to use to generate predictions. (case-insensitive) Supported: "mean", "median", "quantile", "constant". (default = mean)

    Definition Classes
    DummyRegressorParams
  81. final def synchronized[T0](arg0: => T0): T0
    Definition Classes
    AnyRef
  82. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  83. final val tol: DoubleParam
    Definition Classes
    HasTol
  84. def train(dataset: Dataset[_]): DummyRegressionModel
    Attributes
    protected
    Definition Classes
    DummyRegressor → Predictor
  85. def transformSchema(schema: StructType): StructType
    Definition Classes
    Predictor → PipelineStage
  86. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  87. val uid: String
    Definition Classes
    DummyRegressor → Identifiable
  88. def validateAndTransformSchema(schema: StructType, fitting: Boolean, featuresDataType: DataType): StructType
    Attributes
    protected
    Definition Classes
    PredictorParams
  89. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  90. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  91. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException]) @native()
  92. def write: MLWriter
    Definition Classes
    DefaultParamsWritable → MLWritable

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from DummyRegressorParams

Inherited from HasTol

Inherited from Regressor[Vector, DummyRegressor, DummyRegressionModel]

Inherited from Predictor[Vector, DummyRegressor, DummyRegressionModel]

Inherited from PredictorParams

Inherited from HasPredictionCol

Inherited from HasFeaturesCol

Inherited from HasLabelCol

Inherited from Estimator[DummyRegressionModel]

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

getParam

param

setParam

Ungrouped