Packages

c

org.apache.spark.ml

RankerModel

abstract class RankerModel[FeaturesType, M <: RankerModel[FeaturesType, M]] extends PredictionModel[FeaturesType, M] with PredictorParams

Model produced by a Ranker.

FeaturesType

Type of input features. E.g., org.apache.spark.mllib.linalg.Vector

M

Concrete Model type.

Linear Supertypes
PredictionModel[FeaturesType, M], PredictorParams, HasPredictionCol, HasFeaturesCol, HasLabelCol, Model[M], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
Known Subclasses
LightGBMRankerModel
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. RankerModel
  2. PredictionModel
  3. PredictorParams
  4. HasPredictionCol
  5. HasFeaturesCol
  6. HasLabelCol
  7. Model
  8. Transformer
  9. PipelineStage
  10. Logging
  11. Params
  12. Serializable
  13. Serializable
  14. Identifiable
  15. AnyRef
  16. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new RankerModel()

Abstract Value Members

  1. abstract def copy(extra: ParamMap): M
    Definition Classes
    Model → Transformer → PipelineStage → Params
  2. abstract def predict(features: FeaturesType): Double
    Definition Classes
    PredictionModel
    Annotations
    @Since( "2.4.0" )
  3. abstract val uid: String
    Definition Classes
    Identifiable

Concrete Value Members

  1. final def clear(param: Param[_]): RankerModel.this.type
    Definition Classes
    Params
  2. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  3. def explainParams(): String
    Definition Classes
    Params
  4. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  5. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  6. final val featuresCol: Param[String]
    Definition Classes
    HasFeaturesCol
  7. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  8. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  9. final def getFeaturesCol: String
    Definition Classes
    HasFeaturesCol
  10. final def getLabelCol: String
    Definition Classes
    HasLabelCol
  11. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  12. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  13. final def getPredictionCol: String
    Definition Classes
    HasPredictionCol
  14. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  15. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  16. def hasParent: Boolean
    Definition Classes
    Model
  17. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  18. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  19. final val labelCol: Param[String]
    Definition Classes
    HasLabelCol
  20. def numFeatures: Int
    Definition Classes
    PredictionModel
    Annotations
    @Since( "1.6.0" )
  21. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  22. var parent: Estimator[M]
    Definition Classes
    Model
  23. final val predictionCol: Param[String]
    Definition Classes
    HasPredictionCol
  24. final def set[T](param: Param[T], value: T): RankerModel.this.type
    Definition Classes
    Params
  25. def setFeaturesCol(value: String): M
    Definition Classes
    PredictionModel
  26. def setParent(parent: Estimator[M]): M
    Definition Classes
    Model
  27. def setPredictionCol(value: String): M
    Definition Classes
    PredictionModel
  28. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  29. def transform(dataset: Dataset[_]): DataFrame
    Definition Classes
    PredictionModel → Transformer
  30. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  31. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  32. def transformSchema(schema: StructType): StructType
    Definition Classes
    PredictionModel → PipelineStage