Packages

class DummyRegressionModel extends RegressionModel[Vector, DummyRegressionModel] with DummyRegressorParams with MLWritable

Source
DummyRegressor.scala
Linear Supertypes
MLWritable, DummyRegressorParams, HasTol, RegressionModel[Vector, DummyRegressionModel], PredictionModel[Vector, DummyRegressionModel], PredictorParams, HasPredictionCol, HasFeaturesCol, HasLabelCol, Model[DummyRegressionModel], Transformer, PipelineStage, Logging, Params, Serializable, Identifiable, AnyRef, Any
Ordering
  1. Grouped
  2. Alphabetic
  3. By Inheritance
Inherited
  1. DummyRegressionModel
  2. MLWritable
  3. DummyRegressorParams
  4. HasTol
  5. RegressionModel
  6. PredictionModel
  7. PredictorParams
  8. HasPredictionCol
  9. HasFeaturesCol
  10. HasLabelCol
  11. Model
  12. Transformer
  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 DummyRegressionModel(prediction: Double)
  2. new DummyRegressionModel(uid: String, prediction: Double)

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[_]): DummyRegressionModel.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): DummyRegressionModel
    Definition Classes
    DummyRegressionModel → Model → Transformer → 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. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  19. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  20. final val featuresCol: Param[String]
    Definition Classes
    HasFeaturesCol
  21. def featuresDataType: DataType
    Attributes
    protected
    Definition Classes
    PredictionModel
  22. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.Throwable])
  23. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  24. final def getClass(): Class[_ <: AnyRef]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  25. def getConstant: Double

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

    Definition Classes
    DummyRegressorParams
  33. def getStrategy: String
    Definition Classes
    DummyRegressorParams
  34. final def getTol: Double
    Definition Classes
    HasTol
  35. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  36. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  37. def hasParent: Boolean
    Definition Classes
    Model
  38. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  39. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  40. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  41. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  42. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  43. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  44. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  45. final val labelCol: Param[String]
    Definition Classes
    HasLabelCol
  46. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  47. def logDebug(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  48. def logDebug(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  49. def logError(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  50. def logError(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  51. def logInfo(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  52. def logInfo(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  53. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  54. def logTrace(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  55. def logTrace(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  56. def logWarning(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  57. def logWarning(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  58. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  59. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  60. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  61. def numFeatures: Int
    Definition Classes
    PredictionModel
    Annotations
    @Since("1.6.0")
  62. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  63. var parent: Estimator[DummyRegressionModel]
    Definition Classes
    Model
  64. def predict(features: Vector): Double
    Definition Classes
    DummyRegressionModel → PredictionModel
  65. val prediction: Double
  66. final val predictionCol: Param[String]
    Definition Classes
    HasPredictionCol
  67. 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
  68. 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.")
  69. final def set(paramPair: ParamPair[_]): DummyRegressionModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  70. final def set(param: String, value: Any): DummyRegressionModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  71. final def set[T](param: Param[T], value: T): DummyRegressionModel.this.type
    Definition Classes
    Params
  72. def setConstant(value: Double): DummyRegressionModel.this.type

  73. final def setDefault(paramPairs: ParamPair[_]*): DummyRegressionModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  74. final def setDefault[T](param: Param[T], value: T): DummyRegressionModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  75. def setFeaturesCol(value: String): DummyRegressionModel
    Definition Classes
    PredictionModel
  76. def setParent(parent: Estimator[DummyRegressionModel]): DummyRegressionModel
    Definition Classes
    Model
  77. def setPredictionCol(value: String): DummyRegressionModel
    Definition Classes
    PredictionModel
  78. def setQuantile(value: Double): DummyRegressionModel.this.type

  79. def setStrategy(value: String): DummyRegressionModel.this.type

  80. def setTol(value: Double): DummyRegressionModel.this.type

  81. 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
  82. final def synchronized[T0](arg0: => T0): T0
    Definition Classes
    AnyRef
  83. def toString(): String
    Definition Classes
    DummyRegressionModel → Identifiable → AnyRef → Any
  84. final val tol: DoubleParam
    Definition Classes
    HasTol
  85. def transform(dataset: Dataset[_]): DataFrame
    Definition Classes
    PredictionModel → Transformer
  86. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since("2.0.0")
  87. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since("2.0.0") @varargs()
  88. def transformImpl(dataset: Dataset[_]): DataFrame
    Attributes
    protected
    Definition Classes
    PredictionModel
  89. def transformSchema(schema: StructType): StructType
    Definition Classes
    PredictionModel → PipelineStage
  90. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  91. val uid: String
    Definition Classes
    DummyRegressionModel → Identifiable
  92. def validateAndTransformSchema(schema: StructType, fitting: Boolean, featuresDataType: DataType): StructType
    Attributes
    protected
    Definition Classes
    PredictorParams
  93. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  94. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  95. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException]) @native()
  96. def write: MLWriter
    Definition Classes
    DummyRegressionModel → MLWritable

Inherited from MLWritable

Inherited from DummyRegressorParams

Inherited from HasTol

Inherited from RegressionModel[Vector, DummyRegressionModel]

Inherited from PredictionModel[Vector, DummyRegressionModel]

Inherited from PredictorParams

Inherited from HasPredictionCol

Inherited from HasFeaturesCol

Inherited from HasLabelCol

Inherited from Model[DummyRegressionModel]

Inherited from Transformer

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