Trait

org.apache.spark.ml.classification

OpLogisticRegressionParams

Related Doc: package classification

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trait OpLogisticRegressionParams extends LogisticRegressionParams

Linear Supertypes
LogisticRegressionParams, HasAggregationDepth, HasThreshold, HasWeightCol, HasStandardization, HasTol, HasFitIntercept, HasMaxIter, HasElasticNetParam, HasRegParam, ProbabilisticClassifierParams, HasThresholds, HasProbabilityCol, ClassifierParams, HasRawPredictionCol, PredictorParams, HasPredictionCol, HasFeaturesCol, HasLabelCol, Params, Serializable, Serializable, Identifiable, AnyRef, Any
Known Subclasses
OpLogisticRegression
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Inherited
  1. OpLogisticRegressionParams
  2. LogisticRegressionParams
  3. HasAggregationDepth
  4. HasThreshold
  5. HasWeightCol
  6. HasStandardization
  7. HasTol
  8. HasFitIntercept
  9. HasMaxIter
  10. HasElasticNetParam
  11. HasRegParam
  12. ProbabilisticClassifierParams
  13. HasThresholds
  14. HasProbabilityCol
  15. ClassifierParams
  16. HasRawPredictionCol
  17. PredictorParams
  18. HasPredictionCol
  19. HasFeaturesCol
  20. HasLabelCol
  21. Params
  22. Serializable
  23. Serializable
  24. Identifiable
  25. AnyRef
  26. Any
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Abstract Value Members

  1. abstract def copy(extra: ParamMap): Params

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    Definition Classes
    Params

  2. abstract val uid: String

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    Definition Classes
    Identifiable

Concrete 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 val aggregationDepth: IntParam

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    Definition Classes
    HasAggregationDepth

  6. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  7. def checkThresholdConsistency(): Unit

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    Attributes
    protected
    Definition Classes
    LogisticRegressionParams

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

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    Definition Classes
    Params

  9. def clone(): AnyRef

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

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

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    Attributes
    protected
    Definition Classes
    Params

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

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    Attributes
    protected
    Definition Classes
    Params

  12. final val elasticNetParam: DoubleParam

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    Definition Classes
    HasElasticNetParam

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

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    Definition Classes
    AnyRef

  14. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

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

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    Definition Classes
    Params

  16. def explainParams(): String

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    Definition Classes
    Params

  17. final def extractParamMap(): ParamMap

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    Definition Classes
    Params

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

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    Definition Classes
    Params

  19. final val family: Param[String]

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    Definition Classes
    LogisticRegressionParams
    Annotations
    @Since( "2.1.0" )

  20. final val featuresCol: Param[String]

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    Definition Classes
    HasFeaturesCol

  21. def finalize(): Unit

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

  22. final val fitIntercept: BooleanParam

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    Definition Classes
    HasFitIntercept

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

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    Definition Classes
    Params

  24. final def getAggregationDepth: Int

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    Definition Classes
    HasAggregationDepth

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

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    Definition Classes
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  26. final def getDefault[T](param: Param[T]): Option[T]

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    Definition Classes
    Params

  27. final def getElasticNetParam: Double

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    Definition Classes
    HasElasticNetParam

  28. def getFamily: String

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    Definition Classes
    LogisticRegressionParams
    Annotations
    @Since( "2.1.0" )

  29. final def getFeaturesCol: String

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    Definition Classes
    HasFeaturesCol

  30. final def getFitIntercept: Boolean

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    Definition Classes
    HasFitIntercept

  31. final def getLabelCol: String

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    Definition Classes
    HasLabelCol

  32. def getLowerBoundsOnCoefficients: Matrix

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    Definition Classes
    LogisticRegressionParams
    Annotations
    @Since( "2.2.0" )

  33. def getLowerBoundsOnIntercepts: Vector

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    Definition Classes
    LogisticRegressionParams
    Annotations
    @Since( "2.2.0" )

  34. final def getMaxIter: Int

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    Definition Classes
    HasMaxIter

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

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    Definition Classes
    Params

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

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    Definition Classes
    Params

  37. final def getPredictionCol: String

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    Definition Classes
    HasPredictionCol

  38. final def getProbabilityCol: String

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    Definition Classes
    HasProbabilityCol

  39. final def getRawPredictionCol: String

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    Definition Classes
    HasRawPredictionCol

  40. final def getRegParam: Double

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    Definition Classes
    HasRegParam

  41. final def getStandardization: Boolean

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    Definition Classes
    HasStandardization

  42. def getThreshold: Double

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    Definition Classes
    LogisticRegressionParams → HasThreshold

  43. def getThresholds: Array[Double]

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    Definition Classes
    LogisticRegressionParams → HasThresholds

  44. final def getTol: Double

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    Definition Classes
    HasTol

  45. def getUpperBoundsOnCoefficients: Matrix

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    Definition Classes
    LogisticRegressionParams
    Annotations
    @Since( "2.2.0" )

  46. def getUpperBoundsOnIntercepts: Vector

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    Definition Classes
    LogisticRegressionParams
    Annotations
    @Since( "2.2.0" )

  47. final def getWeightCol: String

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    Definition Classes
    HasWeightCol

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

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    Definition Classes
    Params

  49. def hasParam(paramName: String): Boolean

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    Definition Classes
    Params

  50. def hashCode(): Int

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    Definition Classes
    AnyRef → Any

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

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    Definition Classes
    Params

  52. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

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

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    Definition Classes
    Params

  54. final val labelCol: Param[String]

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    Definition Classes
    HasLabelCol

  55. val lowerBoundsOnCoefficients: Param[Matrix]

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    Definition Classes
    LogisticRegressionParams
    Annotations
    @Since( "2.2.0" )

  56. val lowerBoundsOnIntercepts: Param[Vector]

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    Definition Classes
    LogisticRegressionParams
    Annotations
    @Since( "2.2.0" )

  57. final val maxIter: IntParam

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    Definition Classes
    HasMaxIter

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

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    Definition Classes
    AnyRef

  59. final def notify(): Unit

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    Definition Classes
    AnyRef

  60. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

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

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    Definition Classes
    Params

  62. final val predictionCol: Param[String]

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    Definition Classes
    HasPredictionCol

  63. final val probabilityCol: Param[String]

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    Definition Classes
    HasProbabilityCol

  64. final val rawPredictionCol: Param[String]

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    Definition Classes
    HasRawPredictionCol

  65. final val regParam: DoubleParam

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    Definition Classes
    HasRegParam

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

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    Attributes
    protected
    Definition Classes
    Params

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

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    Attributes
    protected
    Definition Classes
    Params

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

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    Definition Classes
    Params

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

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    Attributes
    protected
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    Params

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

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    Attributes
    protected
    Definition Classes
    Params

  71. def setThreshold(value: Double): OpLogisticRegressionParams.this.type

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    Definition Classes
    LogisticRegressionParams

  72. def setThresholds(value: Array[Double]): OpLogisticRegressionParams.this.type

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    Definition Classes
    LogisticRegressionParams

  73. final val standardization: BooleanParam

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    Definition Classes
    HasStandardization

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

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    Definition Classes
    AnyRef

  75. val threshold: DoubleParam

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    Definition Classes
    HasThreshold

  76. final val thresholds: DoubleArrayParam

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    Definition Classes
    HasThresholds

  77. def toString(): String

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    Definition Classes
    Identifiable → AnyRef → Any

  78. final val tol: DoubleParam

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    Definition Classes
    HasTol

  79. val upperBoundsOnCoefficients: Param[Matrix]

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    Definition Classes
    LogisticRegressionParams
    Annotations
    @Since( "2.2.0" )

  80. val upperBoundsOnIntercepts: Param[Vector]

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    Definition Classes
    LogisticRegressionParams
    Annotations
    @Since( "2.2.0" )

  81. def usingBoundConstrainedOptimization: Boolean

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    Attributes
    protected
    Definition Classes
    LogisticRegressionParams

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

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    Attributes
    protected
    Definition Classes
    LogisticRegressionParams → ProbabilisticClassifierParams → ClassifierParams → PredictorParams

  83. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  86. final val weightCol: Param[String]

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    Definition Classes
    HasWeightCol

Inherited from LogisticRegressionParams

Inherited from HasAggregationDepth

Inherited from HasThreshold

Inherited from HasWeightCol

Inherited from HasStandardization

Inherited from HasTol

Inherited from HasFitIntercept

Inherited from HasMaxIter

Inherited from HasElasticNetParam

Inherited from HasRegParam

Inherited from ProbabilisticClassifierParams

Inherited from HasThresholds

Inherited from HasProbabilityCol

Inherited from ClassifierParams

Inherited from HasRawPredictionCol

Inherited from PredictorParams

Inherited from HasPredictionCol

Inherited from HasFeaturesCol

Inherited from HasLabelCol

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

Ungrouped