org.apache.spark.ml.odkl

IsotonicRegression

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
Ordering
  1. Alphabetic
  2. By inheritance
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
  1. Hide All
  2. Show all
Learn more about member selection
Visibility
  1. Public
  2. All

Instance Constructors

  1. new IsotonicRegression()

    Annotations
    @Since( "1.5.0" )

  2. new IsotonicRegression(uid: String)

    Annotations
    @Since( "1.5.0" )

Value Members

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

    Definition Classes
    AnyRef

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

    Definition Classes
    Any

  3. final def ##(): Int

    Definition Classes
    AnyRef → Any

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

    Attributes
    protected
    Definition Classes
    Params

  5. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

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

    Definition Classes
    Any

  7. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  8. final def clear(param: Param[_]): IsotonicRegression.this.type

    Definition Classes
    Params

  9. def clone(): AnyRef

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

  10. def copy(extra: ParamMap): regression.IsotonicRegression

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

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

    Attributes
    protected
    Definition Classes
    Params

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

    Attributes
    protected
    Definition Classes
    Params

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

    Definition Classes
    AnyRef

  14. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

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

    Definition Classes
    Params

  16. def explainParams(): String

    Definition Classes
    Params

  17. final def extractParamMap(): ParamMap

    Definition Classes
    Params

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

    Definition Classes
    Params

  19. def extractWeightedLabeledPoints(dataset: DataFrame): RDD[(Double, Double, Double)]

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

  20. final val featureIndex: IntParam

    Definition Classes
    IsotonicRegressionBase

  21. final val featuresCol: Param[String]

    Definition Classes
    HasFeaturesCol

  22. def finalize(): Unit

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

  23. def fit(dataset: DataFrame): IsotonicRegressionModel

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

  24. def fit(dataset: DataFrame, paramMaps: Array[ParamMap]): Seq[IsotonicRegressionModel]

    Definition Classes
    Estimator

  25. def fit(dataset: DataFrame, paramMap: ParamMap): IsotonicRegressionModel

    Definition Classes
    Estimator

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

    Definition Classes
    Estimator
    Annotations
    @varargs()

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

    Definition Classes
    Params

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

    Definition Classes
    AnyRef → Any

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

    Definition Classes
    Params

  30. final def getFeatureIndex: Int

    Definition Classes
    IsotonicRegressionBase

  31. final def getFeaturesCol: String

    Definition Classes
    HasFeaturesCol

  32. final def getIsotonic: Boolean

    Definition Classes
    IsotonicRegressionBase

  33. final def getLabelCol: String

    Definition Classes
    HasLabelCol

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

    Definition Classes
    Params

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

    Definition Classes
    Params

  36. final def getPredictionCol: String

    Definition Classes
    HasPredictionCol

  37. final def getWeightCol: String

    Definition Classes
    HasWeightCol

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

    Definition Classes
    Params

  39. def hasParam(paramName: String): Boolean

    Definition Classes
    Params

  40. def hasWeightCol: Boolean

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

  41. def hashCode(): Int

    Definition Classes
    AnyRef → Any

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

    Definition Classes
    Params

  43. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

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

    Definition Classes
    Params

  45. def isTraceEnabled(): Boolean

    Attributes
    protected
    Definition Classes
    Logging

  46. final val isotonic: BooleanParam

    Definition Classes
    IsotonicRegressionBase

  47. final val labelCol: Param[String]

    Definition Classes
    HasLabelCol

  48. def log: Logger

    Attributes
    protected
    Definition Classes
    Logging

  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 logInfo(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

  55. def logName: String

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Definition Classes
    AnyRef

  61. final def notify(): Unit

    Definition Classes
    AnyRef

  62. final def notifyAll(): Unit

    Definition Classes
    AnyRef

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

    Definition Classes
    Params

  64. final val predictionCol: Param[String]

    Definition Classes
    HasPredictionCol

  65. def save(path: String): Unit

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

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

    Attributes
    protected
    Definition Classes
    Params

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

    Attributes
    protected
    Definition Classes
    Params

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

    Definition Classes
    Params

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

    Attributes
    protected
    Definition Classes
    Params

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

    Attributes
    protected
    Definition Classes
    Params

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

    Definition Classes
    IsotonicRegression
    Annotations
    @Since( "1.5.0" )

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

    Definition Classes
    IsotonicRegression
    Annotations
    @Since( "1.5.0" )

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

    Definition Classes
    IsotonicRegression
    Annotations
    @Since( "1.5.0" )

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

    Definition Classes
    IsotonicRegression
    Annotations
    @Since( "1.5.0" )

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

    Definition Classes
    IsotonicRegression
    Annotations
    @Since( "1.5.0" )

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

    Definition Classes
    IsotonicRegression
    Annotations
    @Since( "1.5.0" )

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

    Definition Classes
    AnyRef

  78. def toString(): String

    Definition Classes
    Identifiable → AnyRef → Any

  79. def transformSchema(schema: StructType): StructType

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

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

    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()

  81. val uid: String

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

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

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

  83. def validateParams(): Unit

    Definition Classes
    Params

  84. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  87. final val weightCol: Param[String]

    Definition Classes
    HasWeightCol

  88. def write: MLWriter

    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