Class/Object

org.apache.spark.ml.regression

SmileRegressionModel

Related Docs: object SmileRegressionModel | package regression

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class SmileRegressionModel extends RegressionModel[Vector, SmileRegressionModel] with SmileRegressorParams with MLWritable

Linear Supertypes
MLWritable, SmileRegressorParams, RegressionModel[Vector, SmileRegressionModel], PredictionModel[Vector, SmileRegressionModel], PredictorParams, HasPredictionCol, HasFeaturesCol, HasLabelCol, Model[SmileRegressionModel], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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  2. By Inheritance
Inherited
  1. SmileRegressionModel
  2. MLWritable
  3. SmileRegressorParams
  4. RegressionModel
  5. PredictionModel
  6. PredictorParams
  7. HasPredictionCol
  8. HasFeaturesCol
  9. HasLabelCol
  10. Model
  11. Transformer
  12. PipelineStage
  13. Logging
  14. Params
  15. Serializable
  16. Serializable
  17. Identifiable
  18. AnyRef
  19. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new SmileRegressionModel(model: Regression[Array[Double]])

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  2. new SmileRegressionModel(uid: String, model: Regression[Array[Double]])

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Type Members

  1. type Trainer = (Array[Array[Double]], Array[Double]) ⇒ Regression[Array[Double]]

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    Definition Classes
    SmileRegressorParams

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. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  6. final def clear(param: Param[_]): SmileRegressionModel.this.type

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    Definition Classes
    Params

  7. def clone(): AnyRef

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

  8. def copy(extra: ParamMap): SmileRegressionModel

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    Definition Classes
    SmileRegressionModel → Model → Transformer → PipelineStage → Params

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

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    Attributes
    protected
    Definition Classes
    Params

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

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    Attributes
    protected
    Definition Classes
    Params

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

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    Definition Classes
    AnyRef

  12. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

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

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    Definition Classes
    Params

  14. def explainParams(): String

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    Definition Classes
    Params

  15. final def extractParamMap(): ParamMap

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    Definition Classes
    Params

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

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    Definition Classes
    Params

  17. final val featuresCol: Param[String]

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    Definition Classes
    HasFeaturesCol

  18. def featuresDataType: DataType

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    Attributes
    protected
    Definition Classes
    PredictionModel

  19. def finalize(): Unit

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

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

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    Definition Classes
    Params

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

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    Definition Classes
    AnyRef → Any

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

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    Definition Classes
    Params

  23. final def getFeaturesCol: String

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    Definition Classes
    HasFeaturesCol

  24. final def getLabelCol: String

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    Definition Classes
    HasLabelCol

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

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    Definition Classes
    Params

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

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    Definition Classes
    Params

  27. final def getPredictionCol: String

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    Definition Classes
    HasPredictionCol

  28. def getTrainer: Trainer

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    Definition Classes
    SmileRegressorParams

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

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    Definition Classes
    Params

  30. def hasParam(paramName: String): Boolean

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    Definition Classes
    Params

  31. def hasParent: Boolean

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    Definition Classes
    Model

  32. def hashCode(): Int

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    Definition Classes
    AnyRef → Any

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

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    Attributes
    protected
    Definition Classes
    Logging

  34. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Definition Classes
    Params

  36. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

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

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    Definition Classes
    Params

  38. def isTraceEnabled(): Boolean

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    Attributes
    protected
    Definition Classes
    Logging

  39. final val labelCol: Param[String]

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    Definition Classes
    HasLabelCol

  40. def log: Logger

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

  47. def logName: String

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

  52. val model: Regression[Array[Double]]

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

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    Definition Classes
    AnyRef

  54. final def notify(): Unit

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    Definition Classes
    AnyRef

  55. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

  56. def numFeatures: Int

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    Definition Classes
    PredictionModel
    Annotations
    @Since( "1.6.0" )

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

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    Definition Classes
    Params

  58. var parent: Estimator[SmileRegressionModel]

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    Definition Classes
    Model

  59. def predict(features: Vector): Double

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    Definition Classes
    SmileRegressionModel → PredictionModel

  60. final val predictionCol: Param[String]

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    Definition Classes
    HasPredictionCol

  61. def save(path: String): Unit

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

  62. final def set(paramPair: ParamPair[_]): SmileRegressionModel.this.type

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    Attributes
    protected
    Definition Classes
    Params

  63. final def set(param: String, value: Any): SmileRegressionModel.this.type

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    Attributes
    protected
    Definition Classes
    Params

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

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    Definition Classes
    Params

  65. final def setDefault(paramPairs: ParamPair[_]*): SmileRegressionModel.this.type

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    Attributes
    protected
    Definition Classes
    Params

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

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    Attributes
    protected
    Definition Classes
    Params

  67. def setFeaturesCol(value: String): SmileRegressionModel

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    Definition Classes
    PredictionModel

  68. def setParent(parent: Estimator[SmileRegressionModel]): SmileRegressionModel

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    Definition Classes
    Model

  69. def setPredictionCol(value: String): SmileRegressionModel

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    Definition Classes
    PredictionModel

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

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    Definition Classes
    AnyRef

  71. def toString(): String

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    Definition Classes
    Identifiable → AnyRef → Any

  72. val trainer: Param[Trainer]

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    smile regressor used for training

    smile regressor used for training

    Definition Classes
    SmileRegressorParams

  73. def transform(dataset: Dataset[_]): DataFrame

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    Definition Classes
    PredictionModel → Transformer

  74. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame

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    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )

  75. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame

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

  76. def transformImpl(dataset: Dataset[_]): DataFrame

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    Attributes
    protected
    Definition Classes
    PredictionModel

  77. def transformSchema(schema: StructType): StructType

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    Definition Classes
    PredictionModel → PipelineStage

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

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    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()

  79. val uid: String

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    Definition Classes
    SmileRegressionModel → Identifiable

  80. def validateAndTransformSchema(schema: StructType, fitting: Boolean, featuresDataType: DataType): StructType

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    Attributes
    protected
    Definition Classes
    PredictorParams

  81. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  84. def write: MLWriter

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    Definition Classes
    SmileRegressionModel → MLWritable

Inherited from MLWritable

Inherited from SmileRegressorParams

Inherited from RegressionModel[Vector, SmileRegressionModel]

Inherited from PredictionModel[Vector, SmileRegressionModel]

Inherited from PredictorParams

Inherited from HasPredictionCol

Inherited from HasFeaturesCol

Inherited from HasLabelCol

Inherited from Model[SmileRegressionModel]

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

Ungrouped