Trait

ai.catboost.spark

CatBoostPredictorTrait

Related Doc: package spark

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trait CatBoostPredictorTrait[Learner <: Predictor[Vector, Learner, Model], Model <: PredictionModel[Vector, Model]] extends Predictor[Vector, Learner, Model] with DatasetParamsTrait with DefaultParamsWritable

Base trait with common functionality for both CatBoostClassifier and CatBoostRegressor

Self Type
CatBoostPredictorTrait[Learner, Model] with TrainingParamsTrait
Linear Supertypes
DefaultParamsWritable, MLWritable, DatasetParamsTrait, HasWeightCol, Predictor[Vector, Learner, Model], PredictorParams, HasPredictionCol, HasFeaturesCol, HasLabelCol, Estimator[Model], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
Known Subclasses
Ordering
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Inherited
  1. CatBoostPredictorTrait
  2. DefaultParamsWritable
  3. MLWritable
  4. DatasetParamsTrait
  5. HasWeightCol
  6. Predictor
  7. PredictorParams
  8. HasPredictionCol
  9. HasFeaturesCol
  10. HasLabelCol
  11. Estimator
  12. PipelineStage
  13. Logging
  14. Params
  15. Serializable
  16. Serializable
  17. Identifiable
  18. AnyRef
  19. Any
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Visibility
  1. Public
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Abstract Value Members

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

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    Definition Classes
    Predictor → Estimator → PipelineStage → Params
  2. abstract def createModel(fullModel: TFullModel): Model

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    Attributes
    protected
  3. 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
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    Params
  4. final def ==(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  5. def addEstimatedCtrFeatures(quantizedTrainPool: Pool, quantizedEvalPools: Array[Pool], updatedCatBoostJsonParams: JObject, classTargetPreprocessor: Option[TClassTargetPreprocessor] = None, serializedLabelConverter: TVector_i8 = new TVector_i8): (Pool, Array[Pool], CtrsContext)

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    returns

    (preprocessedTrainPool, preprocessedEvalPools, ctrsContext)

    Attributes
    protected
  6. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any
  7. final def clear(param: Param[_]): CatBoostPredictorTrait.this

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    Definition Classes
    Params
  8. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  9. def copyValues[T <: Params](to: T, extra: ParamMap): T

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

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    Attributes
    protected
    Definition Classes
    Params
  11. final def eq(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef
  12. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  13. def explainParam(param: Param[_]): String

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    Definition Classes
    Params
  14. def explainParams(): String

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    Definition Classes
    Params
  15. def extractLabeledPoints(dataset: Dataset[_]): RDD[LabeledPoint]

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    Attributes
    protected
    Definition Classes
    Predictor
  16. final def extractParamMap(): ParamMap

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    Definition Classes
    Params
  17. final def extractParamMap(extra: ParamMap): ParamMap

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    Definition Classes
    Params
  18. final val featuresCol: Param[String]

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    Definition Classes
    HasFeaturesCol
  19. def finalize(): Unit

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    protected[java.lang]
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    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  20. def fit(trainPool: Pool, evalPools: Array[Pool] = Array[Pool]()): Model

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    Additional variant of fit method that accepts CatBoost's Pool s and allows to specify additional datasets for computing evaluation metrics and overfitting detection similarily to CatBoost's other APIs.

    Additional variant of fit method that accepts CatBoost's Pool s and allows to specify additional datasets for computing evaluation metrics and overfitting detection similarily to CatBoost's other APIs.

    trainPool

    The input training dataset.

    evalPools

    The validation datasets used for the following processes:

    • overfitting detector
    • best iteration selection
    • monitoring metrics' changes
    returns

    trained model

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

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    Definition Classes
    Predictor → Estimator
  22. def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[Model]

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  23. def fit(dataset: Dataset[_], paramMap: ParamMap): Model

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  24. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): Model

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

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    Definition Classes
    AnyRef → Any
  27. final def getDefault[T](param: Param[T]): Option[T]

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    Definition Classes
    Params
  28. final def getFeaturesCol: String

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    Definition Classes
    HasFeaturesCol
  29. final def getLabelCol: String

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    Definition Classes
    HasLabelCol
  30. final def getOrDefault[T](param: Param[T]): T

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    Definition Classes
    Params
  31. def getParam(paramName: String): Param[Any]

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    Definition Classes
    Params
  32. final def getPredictionCol: String

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    Definition Classes
    HasPredictionCol
  33. final def getWeightCol: String

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    Definition Classes
    HasWeightCol
  34. final def hasDefault[T](param: Param[T]): Boolean

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    Definition Classes
    Params
  35. def hasParam(paramName: String): Boolean

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    Definition Classes
    Params
  36. def hashCode(): Int

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    Definition Classes
    AnyRef → Any
  37. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

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    Attributes
    protected
    Definition Classes
    Logging
  38. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  39. final def isDefined(param: Param[_]): Boolean

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    Params
  40. final def isInstanceOf[T0]: Boolean

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

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  42. def isTraceEnabled(): Boolean

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    Attributes
    protected
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    Logging
  43. final val labelCol: Param[String]

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    Definition Classes
    HasLabelCol
  44. def log: Logger

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    Attributes
    protected
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    Logging
  45. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

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    Logging
  46. def logDebug(msg: ⇒ String): Unit

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

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    Logging
  48. def logError(msg: ⇒ String): Unit

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

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    Logging
  50. def logInfo(msg: ⇒ String): Unit

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    Logging
  51. def logName: String

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

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    Logging
  53. def logTrace(msg: ⇒ String): Unit

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

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    Logging
  55. def logWarning(msg: ⇒ String): Unit

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    Logging
  56. final def ne(arg0: AnyRef): Boolean

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    AnyRef
  57. final def notify(): Unit

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    AnyRef
  58. final def notifyAll(): Unit

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    Definition Classes
    AnyRef
  59. lazy val params: Array[Param[_]]

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    Definition Classes
    Params
  60. final val predictionCol: Param[String]

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    Definition Classes
    HasPredictionCol
  61. def preprocessBeforeTraining(quantizedTrainPool: Pool, quantizedEvalPools: Array[Pool]): (Pool, Array[Pool], CatBoostTrainingContext)

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    override in descendants if necessary

    override in descendants if necessary

    returns

    (preprocessedTrainPool, preprocessedEvalPools, catBoostTrainingContext)

    Attributes
    protected
  62. def save(path: String): Unit

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    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  63. final def set(paramPair: ParamPair[_]): CatBoostPredictorTrait.this

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    Attributes
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    Params
  64. final def set(param: String, value: Any): CatBoostPredictorTrait.this

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    Attributes
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    Definition Classes
    Params
  65. final def set[T](param: Param[T], value: T): CatBoostPredictorTrait.this

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    Definition Classes
    Params
  66. final def setDefault(paramPairs: ParamPair[_]*): CatBoostPredictorTrait.this

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    Attributes
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    Params
  67. final def setDefault[T](param: Param[T], value: T): CatBoostPredictorTrait.this

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    Attributes
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    Params
  68. def setFeaturesCol(value: String): Learner

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    Definition Classes
    Predictor
  69. def setLabelCol(value: String): Learner

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    Definition Classes
    Predictor
  70. def setPredictionCol(value: String): Learner

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    Definition Classes
    Predictor
  71. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef
  72. def toString(): String

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    Definition Classes
    Identifiable → AnyRef → Any
  73. def train(dataset: Dataset[_]): Model

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    Attributes
    protected
    Definition Classes
    CatBoostPredictorTrait → Predictor
  74. def transformSchema(schema: StructType): StructType

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    Definition Classes
    Predictor → PipelineStage
  75. def transformSchema(schema: StructType, logging: Boolean): StructType

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    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  76. def validateAndTransformSchema(schema: StructType, fitting: Boolean, featuresDataType: DataType): StructType

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    Attributes
    protected
    Definition Classes
    PredictorParams
  77. final def wait(): Unit

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    AnyRef
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    @throws( ... )
  78. final def wait(arg0: Long, arg1: Int): Unit

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    @throws( ... )
  79. final def wait(arg0: Long): Unit

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    @throws( ... )
  80. final val weightCol: Param[String]

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    Definition Classes
    HasWeightCol
  81. def write: MLWriter

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    Definition Classes
    DefaultParamsWritable → MLWritable

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from DatasetParamsTrait

Inherited from HasWeightCol

Inherited from Predictor[Vector, Learner, Model]

Inherited from PredictorParams

Inherited from HasPredictionCol

Inherited from HasFeaturesCol

Inherited from HasLabelCol

Inherited from Estimator[Model]

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