Packages

t

ai.catboost.spark

CatBoostPredictorTrait

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, Identifiable, AnyRef, Any
Known Subclasses
CatBoostClassifier, CatBoostRegressor
Ordering
  1. Alphabetic
  2. By Inheritance
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. Identifiable
  17. AnyRef
  18. Any
  1. Hide All
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Visibility
  1. Public
  2. Protected

Abstract Value Members

  1. abstract def copy(extra: ParamMap): Learner
    Definition Classes
    Predictor → Estimator → PipelineStage → Params
  2. abstract def createModel(fullModel: TFullModel): Model
    Attributes
    protected
  3. abstract val uid: String
    Definition Classes
    Identifiable

Concrete Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##: Int
    Definition Classes
    AnyRef → Any
  3. final def $[T](param: Param[T]): T
    Attributes
    protected
    Definition Classes
    Params
  4. final def ==(arg0: Any): Boolean
    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)

    returns

    (preprocessedTrainPool, preprocessedEvalPools, ctrsContext)

    Attributes
    protected
  6. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  7. final def clear(param: Param[_]): CatBoostPredictorTrait.this
    Definition Classes
    Params
  8. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.CloneNotSupportedException]) @native()
  9. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  10. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  11. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  12. def equals(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef → Any
  13. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  14. def explainParams(): String
    Definition Classes
    Params
  15. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  16. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  17. final val featuresCol: Param[String]
    Definition Classes
    HasFeaturesCol
  18. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.Throwable])
  19. def fit(trainPool: Pool, evalPools: Array[Pool] = Array[Pool]()): Model

    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

  20. def fit(dataset: Dataset[_]): Model
    Definition Classes
    Predictor → Estimator
  21. def fit(dataset: Dataset[_], paramMaps: Seq[ParamMap]): Seq[Model]
    Definition Classes
    Estimator
    Annotations
    @Since("2.0.0")
  22. def fit(dataset: Dataset[_], paramMap: ParamMap): Model
    Definition Classes
    Estimator
    Annotations
    @Since("2.0.0")
  23. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): Model
    Definition Classes
    Estimator
    Annotations
    @Since("2.0.0") @varargs()
  24. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  25. final def getClass(): Class[_ <: AnyRef]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  26. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  27. final def getFeaturesCol: String
    Definition Classes
    HasFeaturesCol
  28. final def getLabelCol: String
    Definition Classes
    HasLabelCol
  29. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  30. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  31. final def getPredictionCol: String
    Definition Classes
    HasPredictionCol
  32. final def getWeightCol: String
    Definition Classes
    HasWeightCol
  33. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  34. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  35. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  36. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  37. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  38. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  39. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  40. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  41. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  42. final val labelCol: Param[String]
    Definition Classes
    HasLabelCol
  43. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  44. def logDebug(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  45. def logDebug(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  46. def logError(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  47. def logError(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  48. def logInfo(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  49. def logInfo(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  50. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  51. def logTrace(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  52. def logTrace(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  53. def logWarning(msg: => String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  54. def logWarning(msg: => String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  55. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  56. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  57. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  58. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  59. final val predictionCol: Param[String]
    Definition Classes
    HasPredictionCol
  60. def preprocessBeforeTraining(quantizedTrainPool: Pool, quantizedEvalPools: Array[Pool]): (Pool, Array[Pool], CatBoostTrainingContext)

    override in descendants if necessary

    override in descendants if necessary

    returns

    (preprocessedTrainPool, preprocessedEvalPools, catBoostTrainingContext)

    Attributes
    protected
  61. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since("1.6.0") @throws("If the input path already exists but overwrite is not enabled.")
  62. final def set(paramPair: ParamPair[_]): CatBoostPredictorTrait.this
    Attributes
    protected
    Definition Classes
    Params
  63. final def set(param: String, value: Any): CatBoostPredictorTrait.this
    Attributes
    protected
    Definition Classes
    Params
  64. final def set[T](param: Param[T], value: T): CatBoostPredictorTrait.this
    Definition Classes
    Params
  65. final def setDefault(paramPairs: ParamPair[_]*): CatBoostPredictorTrait.this
    Attributes
    protected
    Definition Classes
    Params
  66. final def setDefault[T](param: Param[T], value: T): CatBoostPredictorTrait.this
    Attributes
    protected[ml]
    Definition Classes
    Params
  67. def setFeaturesCol(value: String): Learner
    Definition Classes
    Predictor
  68. def setLabelCol(value: String): Learner
    Definition Classes
    Predictor
  69. def setPredictionCol(value: String): Learner
    Definition Classes
    Predictor
  70. final def synchronized[T0](arg0: => T0): T0
    Definition Classes
    AnyRef
  71. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  72. def train(dataset: Dataset[_]): Model
    Attributes
    protected
    Definition Classes
    CatBoostPredictorTrait → Predictor
  73. def transformSchema(schema: StructType): StructType
    Definition Classes
    Predictor → PipelineStage
  74. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  75. def validateAndTransformSchema(schema: StructType, fitting: Boolean, featuresDataType: DataType): StructType
    Attributes
    protected
    Definition Classes
    PredictorParams
  76. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  77. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  78. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException]) @native()
  79. final val weightCol: Param[String]
    Definition Classes
    HasWeightCol
  80. def write: MLWriter
    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 Identifiable

Inherited from AnyRef

Inherited from Any

Ungrouped