org.apache.spark.ml.odkl.CombinedModel

LinearCombinationModelLearner

class LinearCombinationModelLearner[M <: ModelWithSummary[M]] extends PerClassModelLearner[M, LinearCombinationModel[M]]

Trains a model which predicts a scalar of weighted classes or a vector which is a generalized linear combination of per-class predictions

Linear Supertypes
PerClassModelLearner[M, LinearCombinationModel[M]], HasPredictionCol, HasLabelCol, HasClassesWeights, HasClassesCol, ForkedEstimator[M, String, LinearCombinationModel[M]], ForkedModelParams, SummarizableEstimator[LinearCombinationModel[M]], Estimator[LinearCombinationModel[M]], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. LinearCombinationModelLearner
  2. PerClassModelLearner
  3. HasPredictionCol
  4. HasLabelCol
  5. HasClassesWeights
  6. HasClassesCol
  7. ForkedEstimator
  8. ForkedModelParams
  9. SummarizableEstimator
  10. Estimator
  11. PipelineStage
  12. Logging
  13. Params
  14. Serializable
  15. Serializable
  16. Identifiable
  17. AnyRef
  18. Any
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Instance Constructors

  1. new LinearCombinationModelLearner(nested: SummarizableEstimator[M])

  2. new LinearCombinationModelLearner(nested: SummarizableEstimator[M], uid: String)

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 val cacheForks: Param[Boolean]

    Definition Classes
    ForkedEstimator

  9. final val classesColumn: Param[String]

    Definition Classes
    HasClassesCol

  10. final val classesMap: JacksonParam[Map[String, String]]

    Definition Classes
    PerClassModelLearner

  11. final val classesToIgnore: JacksonParam[Set[String]]

    Definition Classes
    PerClassModelLearner

  12. final val classesWeights: JacksonParam[Map[String, Double]]

    Definition Classes
    HasClassesWeights

  13. final def clear(param: Param[_]): LinearCombinationModelLearner.this.type

    Definition Classes
    Params

  14. def clone(): AnyRef

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

  15. def copy(extra: ParamMap): SummarizableEstimator[LinearCombinationModel[M]]

    Definition Classes
    LinearCombinationModelLearner → SummarizableEstimator → Estimator → PipelineStage → Params

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

    Attributes
    protected
    Definition Classes
    Params

  17. def createForks(dataset: DataFrame): Seq[(String, DataFrame)]

    Override this method and create forks to train from the data.

    Override this method and create forks to train from the data.

    Definition Classes
    PerClassModelLearner → ForkedEstimator

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

    Attributes
    protected
    Definition Classes
    Params

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

    Definition Classes
    AnyRef

  20. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

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

    Definition Classes
    Params

  22. def explainParams(): String

    Definition Classes
    Params

  23. final def extractParamMap(): ParamMap

    Definition Classes
    Params

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

    Definition Classes
    Params

  25. def finalize(): Unit

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

  26. def fit(dataset: DataFrame): LinearCombinationModel[M]

    Definition Classes
    ForkedEstimator → Estimator

  27. def fit(dataset: DataFrame, paramMaps: Array[ParamMap]): Seq[LinearCombinationModel[M]]

    Definition Classes
    Estimator

  28. def fit(dataset: DataFrame, paramMap: ParamMap): LinearCombinationModel[M]

    Definition Classes
    Estimator

  29. def fit(dataset: DataFrame, firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): LinearCombinationModel[M]

    Definition Classes
    Estimator
    Annotations
    @varargs()

  30. def fitFork(wholeData: DataFrame, partialData: (String, DataFrame)): (String, M)

    Definition Classes
    ForkedEstimator

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

    Definition Classes
    Params

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

    Definition Classes
    AnyRef → Any

  33. def getClassesWeights: Map[String, Double]

    Definition Classes
    HasClassesWeights

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

    Definition Classes
    Params

  35. final def getLabelCol: String

    Definition Classes
    HasLabelCol

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

    Definition Classes
    Params

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

    Definition Classes
    Params

  38. final def getPredictionCol: String

    Definition Classes
    HasPredictionCol

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

    Definition Classes
    Params

  40. def hasParam(paramName: String): Boolean

    Definition Classes
    Params

  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 labelCol: Param[String]

    Definition Classes
    HasLabelCol

  47. def log: Logger

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

  54. def logName: String

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

  59. def mayBePropagateKey(data: DataFrame, key: Any): DataFrame

    Attributes
    protected
    Definition Classes
    ForkedModelParams

  60. def mergeModels(models: Seq[(String, M)]): LinearCombinationModel[M]

    Given models trained for each fork create a combined model.

    Given models trained for each fork create a combined model. This model is the result of the estimator.

    Attributes
    protected
    Definition Classes
    LinearCombinationModelLearner → ForkedEstimator

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

    Definition Classes
    AnyRef

  62. final def notify(): Unit

    Definition Classes
    AnyRef

  63. final def notifyAll(): Unit

    Definition Classes
    AnyRef

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

    Definition Classes
    Params

  65. final val pathForTempModels: Param[String]

    Definition Classes
    ForkedEstimator

  66. final val predictionCol: Param[String]

    Definition Classes
    HasPredictionCol

  67. final val propagatedKeyColumn: Param[String]

    Definition Classes
    ForkedModelParams

  68. final def set(paramPair: ParamPair[_]): LinearCombinationModelLearner.this.type

    Attributes
    protected
    Definition Classes
    Params

  69. final def set(param: String, value: Any): LinearCombinationModelLearner.this.type

    Attributes
    protected
    Definition Classes
    Params

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

    Definition Classes
    Params

  71. def setCacheForks(value: Boolean): LinearCombinationModelLearner.this.type

    Definition Classes
    ForkedEstimator

  72. def setClassesColumn(value: String): LinearCombinationModelLearner.this.type

    Definition Classes
    HasClassesCol

  73. def setClassesMap(values: (String, String)*): LinearCombinationModelLearner.this.type

    Definition Classes
    PerClassModelLearner

  74. def setClassesToIgnore(values: String*): LinearCombinationModelLearner.this.type

    Definition Classes
    PerClassModelLearner

  75. def setClassesWeights(weights: (String, Double)*): LinearCombinationModelLearner.this.type

    Definition Classes
    HasClassesWeights

  76. final def setDefault(paramPairs: ParamPair[_]*): LinearCombinationModelLearner.this.type

    Attributes
    protected
    Definition Classes
    Params

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

    Attributes
    protected
    Definition Classes
    Params

  78. def setPathForTempModels(value: String): LinearCombinationModelLearner.this.type

    Definition Classes
    ForkedEstimator

  79. def setPredictionCol(value: String): LinearCombinationModelLearner.this.type

    Definition Classes
    PerClassModelLearner

  80. def setPropagatedKeyColumn(value: String): LinearCombinationModelLearner.this.type

    Definition Classes
    ForkedModelParams

  81. def setTrainParallel(value: Boolean): LinearCombinationModelLearner.this.type

    Definition Classes
    ForkedEstimator

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

    Definition Classes
    AnyRef

  83. def toString(): String

    Definition Classes
    Identifiable → AnyRef → Any

  84. final val trainParallel: Param[Boolean]

    Definition Classes
    ForkedEstimator

  85. def transformSchema(schema: StructType): StructType

    Definition Classes
    ForkedEstimator → PipelineStage
    Annotations
    @DeveloperApi()

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

    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()

  87. val uid: String

    Definition Classes
    LinearCombinationModelLearner → PerClassModelLearner → ForkedEstimator → Identifiable

  88. def validateParams(): Unit

    Definition Classes
    Params

  89. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from PerClassModelLearner[M, LinearCombinationModel[M]]

Inherited from HasPredictionCol

Inherited from HasLabelCol

Inherited from HasClassesWeights

Inherited from HasClassesCol

Inherited from ForkedEstimator[M, String, LinearCombinationModel[M]]

Inherited from ForkedModelParams

Inherited from SummarizableEstimator[LinearCombinationModel[M]]

Inherited from Estimator[LinearCombinationModel[M]]

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