Class/Object

org.apache.spark.ml.odkl

IsotonicRegression

Related Docs: object IsotonicRegression | package odkl

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class IsotonicRegression extends regression.IsotonicRegression

:: Experimental :: Isotonic regression.

Currently implemented using parallelized pool adjacent violators algorithm. Only univariate (single feature) algorithm supported.

Uses org.apache.spark.mllib.regression.IsotonicRegression.

ODKL Patch: Used to inject our patched mllib implementation.

Annotations
@Since( "1.5.0" ) @Experimental()
Linear Supertypes
regression.IsotonicRegression, DefaultParamsWritable, MLWritable, IsotonicRegressionBase, HasWeightCol, HasPredictionCol, HasLabelCol, HasFeaturesCol, Estimator[IsotonicRegressionModel], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. IsotonicRegression
  2. IsotonicRegression
  3. DefaultParamsWritable
  4. MLWritable
  5. IsotonicRegressionBase
  6. HasWeightCol
  7. HasPredictionCol
  8. HasLabelCol
  9. HasFeaturesCol
  10. Estimator
  11. PipelineStage
  12. Logging
  13. Params
  14. Serializable
  15. Serializable
  16. Identifiable
  17. AnyRef
  18. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new IsotonicRegression()

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    Annotations
    @Since( "1.5.0" )

  2. new IsotonicRegression(uid: String)

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    Annotations
    @Since( "1.5.0" )

Value Members

  1. final def !=(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

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  3. final def $[T](param: Param[T]): T

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  4. final def ==(arg0: Any): Boolean

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  5. final def asInstanceOf[T0]: T0

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    Any

  6. final def clear(param: Param[_]): IsotonicRegression.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): regression.IsotonicRegression

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    Definition Classes
    IsotonicRegression → Estimator → PipelineStage → Params
    Annotations
    @Since( "1.5.0" )

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

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    Params

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

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

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    AnyRef

  12. def equals(arg0: Any): Boolean

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

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    Params

  14. def explainParams(): String

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    Definition Classes
    Params

  15. final def extractParamMap(): ParamMap

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    Params

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

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    Definition Classes
    Params

  17. def extractWeightedLabeledPoints(dataset: Dataset[_]): RDD[(Double, Double, Double)]

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    Attributes
    protected[org.apache.spark.ml]
    Definition Classes
    IsotonicRegressionBase

  18. final val featureIndex: IntParam

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    Definition Classes
    IsotonicRegressionBase

  19. final val featuresCol: Param[String]

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    Definition Classes
    HasFeaturesCol

  20. def finalize(): Unit

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    protected[java.lang]
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    AnyRef
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    @throws( classOf[java.lang.Throwable] )

  21. def fit(dataset: Dataset[_]): IsotonicRegressionModel

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    Definition Classes
    IsotonicRegression → IsotonicRegression → Estimator
    Annotations
    @Since( "1.5.0" )

  22. def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[IsotonicRegressionModel]

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )

  23. def fit(dataset: Dataset[_], paramMap: ParamMap): IsotonicRegressionModel

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )

  24. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): IsotonicRegressionModel

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

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

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    Params

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

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

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    Definition Classes
    Params

  28. final def getFeatureIndex: Int

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    Definition Classes
    IsotonicRegressionBase

  29. final def getFeaturesCol: String

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    Definition Classes
    HasFeaturesCol

  30. final def getIsotonic: Boolean

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    Definition Classes
    IsotonicRegressionBase

  31. final def getLabelCol: String

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    Definition Classes
    HasLabelCol

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

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    Params

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

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    Params

  34. final def getPredictionCol: String

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    Definition Classes
    HasPredictionCol

  35. final def getWeightCol: String

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    Definition Classes
    HasWeightCol

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

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    Params

  37. def hasParam(paramName: String): Boolean

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  38. def hashCode(): Int

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

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    protected
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    Logging

  40. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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    Logging

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

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  42. final def isInstanceOf[T0]: Boolean

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

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  44. def isTraceEnabled(): Boolean

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    Logging

  45. final val isotonic: BooleanParam

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    Definition Classes
    IsotonicRegressionBase

  46. final val labelCol: Param[String]

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    Definition Classes
    HasLabelCol

  47. def log: Logger

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    Logging

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

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

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    Logging

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

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

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

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

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  54. def logName: String

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

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    Logging

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

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    Logging

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

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

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    Logging

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

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  60. final def notify(): Unit

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  61. final def notifyAll(): Unit

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    AnyRef

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

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    Params

  63. final val predictionCol: Param[String]

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    Definition Classes
    HasPredictionCol

  64. def save(path: String): Unit

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

  65. final def set(paramPair: ParamPair[_]): IsotonicRegression.this.type

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  66. final def set(param: String, value: Any): IsotonicRegression.this.type

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

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    Params

  68. final def setDefault(paramPairs: ParamPair[_]*): IsotonicRegression.this.type

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

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    protected
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    Params

  70. def setFeatureIndex(value: Int): IsotonicRegression.this.type

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    Definition Classes
    IsotonicRegression
    Annotations
    @Since( "1.5.0" )

  71. def setFeaturesCol(value: String): IsotonicRegression.this.type

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    Definition Classes
    IsotonicRegression
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    @Since( "1.5.0" )

  72. def setIsotonic(value: Boolean): IsotonicRegression.this.type

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    Definition Classes
    IsotonicRegression
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    @Since( "1.5.0" )

  73. def setLabelCol(value: String): IsotonicRegression.this.type

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    Definition Classes
    IsotonicRegression
    Annotations
    @Since( "1.5.0" )

  74. def setPredictionCol(value: String): IsotonicRegression.this.type

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    Definition Classes
    IsotonicRegression
    Annotations
    @Since( "1.5.0" )

  75. def setWeightCol(value: String): IsotonicRegression.this.type

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    Definition Classes
    IsotonicRegression
    Annotations
    @Since( "1.5.0" )

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

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    AnyRef

  77. def toString(): String

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    Identifiable → AnyRef → Any

  78. def transformSchema(schema: StructType): StructType

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    IsotonicRegression → PipelineStage
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    @Since( "1.5.0" )

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

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    protected
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    PipelineStage
    Annotations
    @DeveloperApi()

  80. val uid: String

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    Definition Classes
    IsotonicRegression → IsotonicRegression → Identifiable
    Annotations
    @Since( "1.5.0" )

  81. def validateAndTransformSchema(schema: StructType, fitting: Boolean): StructType

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    Attributes
    protected[org.apache.spark.ml]
    Definition Classes
    IsotonicRegressionBase

  82. final def wait(): Unit

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    @throws( ... )

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

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    @throws( ... )

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

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    @throws( ... )

  85. final val weightCol: Param[String]

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    Definition Classes
    HasWeightCol

  86. def write: MLWriter

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    Definition Classes
    DefaultParamsWritable → MLWritable

Inherited from regression.IsotonicRegression

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from IsotonicRegressionBase

Inherited from HasWeightCol

Inherited from HasPredictionCol

Inherited from HasLabelCol

Inherited from HasFeaturesCol

Inherited from Estimator[IsotonicRegressionModel]

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

Ungrouped