Packages

  • package root
    Definition Classes
    root
  • package ai
    Definition Classes
    root
  • package catboost
    Definition Classes
    ai
  • package spark

    CatBoost is a machine learning algorithm that uses gradient boosting on decision trees.

    CatBoost is a machine learning algorithm that uses gradient boosting on decision trees.

    Overview

    This package provides classes that implement interfaces from Apache Spark Machine Learning Library (MLLib).

    For binary and multi- classification problems use CatBoostClassifier, for regression use CatBoostRegressor.

    These classes implement usual fit method of org.apache.spark.ml.Predictor that accept a single org.apache.spark.sql.DataFrame for training, but you can also use other fit method that accepts additional datasets for computing evaluation metrics and overfitting detection similarily to CatBoost's other APIs.

    This package also contains Pool class that is CatBoost's abstraction of a dataset. It contains additional information compared to simple org.apache.spark.sql.DataFrame.

    It is also possible to create Pool with quantized features before training by calling quantize method. This is useful if this dataset is used for training multiple times and quantization parameters do not change. Pre-quantized Pool allows to cache quantized features data and so do not re-run feature quantization step at the start of an each training.

    Detailed documentation is available on https://catboost.ai/docs/

    Definition Classes
    catboost
  • package params
    Definition Classes
    spark
  • CatBoostClassificationModel
  • CatBoostClassifier
  • CatBoostPredictorTrait
  • CatBoostRegressionModel
  • CatBoostRegressor
  • Pool

class CatBoostRegressor extends CatBoostRegressorBase[Vector, CatBoostRegressor, CatBoostRegressionModel] with CatBoostPredictorTrait[CatBoostRegressor, CatBoostRegressionModel] with RegressorTrainingParamsTrait

Class to train CatBoostRegressionModel The default optimized loss function is RMSE

Examples

Basic example.

val spark = SparkSession.builder()
  .master("local[*]")
  .appName("RegressorTest")
  .getOrCreate();

val srcDataSchema = Seq(
  StructField("features", SQLDataTypes.VectorType),
  StructField("label", StringType)
)

val trainData = Seq(
  Row(Vectors.dense(0.1, 0.2, 0.11), "0.12"),
  Row(Vectors.dense(0.97, 0.82, 0.33), "0.22"),
  Row(Vectors.dense(0.13, 0.22, 0.23), "0.34"),
  Row(Vectors.dense(0.8, 0.62, 0.0), "0.1")
)

val trainDf = spark.createDataFrame(spark.sparkContext.parallelize(trainData), StructType(srcDataSchema))
val trainPool = new Pool(trainDf)

val evalData = Seq(
  Row(Vectors.dense(0.22, 0.33, 0.9), "0.1"),
  Row(Vectors.dense(0.11, 0.1, 0.21), "0.9"),
  Row(Vectors.dense(0.77, 0.0, 0.0), "0.72")
)

val evalDf = spark.createDataFrame(spark.sparkContext.parallelize(evalData), StructType(srcDataSchema))
val evalPool = new Pool(evalDf)

val regressor = new CatBoostRegressor
val model = regressor.fit(trainPool, Array[Pool](evalPool))
val predictions = model.transform(evalPool.data)
predictions.show()

Example with alternative loss function.

...<initialize trainPool, evalPool>
val regressor = new CatBoostRegressor().setLossFunction("MAE")
val model = regressor.fit(trainPool, Array[Pool](evalPool))
val predictions = model.transform(evalPool.data)
predictions.show()

Serialization

Supports standard Spark MLLib serialization. Data can be saved to distributed filesystem like HDFS or local files.

Examples:

Save:

val regressor = new CatBoostRegressor().setLossFunction("MAE")
val path = "/home/user/catboost_regressors/regressor0"
regressor.write.save(path)

Load:

val path = "/home/user/catboost_regressors/regressor0"
val regressor = CatBoostRegressor.load(path)
val trainPool : Pool = ... init Pool ...
val model = regressor.fit(trainPool)
Linear Supertypes
RegressorTrainingParamsTrait, TrainingParamsTrait, QuantizationParamsTrait, ThreadCountParams, IgnoredFeaturesParams, CatBoostPredictorTrait[CatBoostRegressor, CatBoostRegressionModel], DefaultParamsWritable, MLWritable, DatasetParamsTrait, HasWeightCol, CatBoostRegressorBase[Vector, CatBoostRegressor, CatBoostRegressionModel], Regressor[Vector, CatBoostRegressor, CatBoostRegressionModel], Predictor[Vector, CatBoostRegressor, CatBoostRegressionModel], PredictorParams, HasPredictionCol, HasFeaturesCol, HasLabelCol, Estimator[CatBoostRegressionModel], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
Ordering
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  2. By Inheritance
Inherited
  1. CatBoostRegressor
  2. RegressorTrainingParamsTrait
  3. TrainingParamsTrait
  4. QuantizationParamsTrait
  5. ThreadCountParams
  6. IgnoredFeaturesParams
  7. CatBoostPredictorTrait
  8. DefaultParamsWritable
  9. MLWritable
  10. DatasetParamsTrait
  11. HasWeightCol
  12. CatBoostRegressorBase
  13. Regressor
  14. Predictor
  15. PredictorParams
  16. HasPredictionCol
  17. HasFeaturesCol
  18. HasLabelCol
  19. Estimator
  20. PipelineStage
  21. Logging
  22. Params
  23. Serializable
  24. Serializable
  25. Identifiable
  26. AnyRef
  27. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new CatBoostRegressor()
  2. new CatBoostRegressor(uid: String)

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. final val allowConstLabel: BooleanParam
    Definition Classes
    TrainingParamsTrait
  6. final val allowWritingFiles: BooleanParam
    Definition Classes
    TrainingParamsTrait
  7. final val approxOnFullHistory: BooleanParam
    Definition Classes
    TrainingParamsTrait
  8. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  9. final val baggingTemperature: FloatParam
    Definition Classes
    TrainingParamsTrait
  10. final val bestModelMinTrees: IntParam
    Definition Classes
    TrainingParamsTrait
  11. final val bootstrapType: EnumParam[EBootstrapType]
    Definition Classes
    TrainingParamsTrait
  12. final val borderCount: IntParam
    Definition Classes
    QuantizationParamsTrait
  13. final def clear(param: Param[_]): CatBoostRegressor.this.type
    Definition Classes
    Params
  14. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  15. def copy(extra: ParamMap): CatBoostRegressor
    Definition Classes
    CatBoostRegressor → Predictor → Estimator → PipelineStage → Params
  16. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  17. def createModel(nativeModel: TFullModel): CatBoostRegressionModel
    Attributes
    protected
    Definition Classes
    CatBoostRegressor → CatBoostPredictorTrait
  18. final val customMetric: StringArrayParam
    Definition Classes
    TrainingParamsTrait
  19. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  20. final val depth: IntParam
    Definition Classes
    TrainingParamsTrait
  21. final val diffusionTemperature: FloatParam
    Definition Classes
    TrainingParamsTrait
  22. final val earlyStoppingRounds: IntParam
    Definition Classes
    TrainingParamsTrait
  23. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  24. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  25. final val evalMetric: Param[String]
    Definition Classes
    TrainingParamsTrait
  26. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  27. def explainParams(): String
    Definition Classes
    Params
  28. def extractLabeledPoints(dataset: Dataset[_]): RDD[LabeledPoint]
    Attributes
    protected
    Definition Classes
    Predictor
  29. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  30. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  31. final val featureBorderType: EnumParam[EBorderSelectionType]
    Definition Classes
    QuantizationParamsTrait
  32. final val featureWeightsList: DoubleArrayParam
    Definition Classes
    TrainingParamsTrait
  33. final val featureWeightsMap: OrderedStringMapParam[Float]
    Definition Classes
    TrainingParamsTrait
  34. final val featuresCol: Param[String]
    Definition Classes
    HasFeaturesCol
  35. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  36. final val firstFeatureUsePenaltiesList: DoubleArrayParam
    Definition Classes
    TrainingParamsTrait
  37. final val firstFeatureUsePenaltiesMap: OrderedStringMapParam[Float]
    Definition Classes
    TrainingParamsTrait
  38. def fit(trainPool: Pool, evalPools: Array[Pool] = Array[Pool]()): CatBoostRegressionModel

    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

    Definition Classes
    CatBoostPredictorTrait
  39. def fit(dataset: Dataset[_]): CatBoostRegressionModel
    Definition Classes
    Predictor → Estimator
  40. def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[CatBoostRegressionModel]
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  41. def fit(dataset: Dataset[_], paramMap: ParamMap): CatBoostRegressionModel
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  42. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): CatBoostRegressionModel
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" ) @varargs()
  43. final val foldLenMultiplier: FloatParam
    Definition Classes
    TrainingParamsTrait
  44. final val foldPermutationBlock: IntParam
    Definition Classes
    TrainingParamsTrait
  45. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  46. final def getAllowConstLabel: Boolean
    Definition Classes
    TrainingParamsTrait
  47. final def getAllowWritingFiles: Boolean
    Definition Classes
    TrainingParamsTrait
  48. final def getApproxOnFullHistory: Boolean
    Definition Classes
    TrainingParamsTrait
  49. final def getBaggingTemperature: Float
    Definition Classes
    TrainingParamsTrait
  50. final def getBestModelMinTrees: Int
    Definition Classes
    TrainingParamsTrait
  51. final def getBootstrapType: EBootstrapType
    Definition Classes
    TrainingParamsTrait
  52. final def getBorderCount: Int
    Definition Classes
    QuantizationParamsTrait
  53. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  54. final def getCustomMetric: Array[String]
    Definition Classes
    TrainingParamsTrait
  55. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  56. final def getDepth: Int
    Definition Classes
    TrainingParamsTrait
  57. final def getDiffusionTemperature: Float
    Definition Classes
    TrainingParamsTrait
  58. final def getEarlyStoppingRounds: Int
    Definition Classes
    TrainingParamsTrait
  59. final def getEvalMetric: String
    Definition Classes
    TrainingParamsTrait
  60. final def getFeatureBorderType: EBorderSelectionType
    Definition Classes
    QuantizationParamsTrait
  61. final def getFeatureWeightsList: Array[Double]
    Definition Classes
    TrainingParamsTrait
  62. final def getFeatureWeightsMap: LinkedHashMap[String, Float]
    Definition Classes
    TrainingParamsTrait
  63. final def getFeaturesCol: String
    Definition Classes
    HasFeaturesCol
  64. final def getFirstFeatureUsePenaltiesList: Array[Double]
    Definition Classes
    TrainingParamsTrait
  65. final def getFirstFeatureUsePenaltiesMap: LinkedHashMap[String, Float]
    Definition Classes
    TrainingParamsTrait
  66. final def getFoldLenMultiplier: Float
    Definition Classes
    TrainingParamsTrait
  67. final def getFoldPermutationBlock: Int
    Definition Classes
    TrainingParamsTrait
  68. final def getHasTime: Boolean
    Definition Classes
    TrainingParamsTrait
  69. final def getIgnoredFeaturesIndices: Array[Int]
    Definition Classes
    IgnoredFeaturesParams
  70. final def getIgnoredFeaturesNames: Array[String]
    Definition Classes
    IgnoredFeaturesParams
  71. final def getInputBorders: String
    Definition Classes
    QuantizationParamsTrait
  72. final def getIterations: Int
    Definition Classes
    TrainingParamsTrait
  73. final def getL2LeafReg: Float
    Definition Classes
    TrainingParamsTrait
  74. final def getLabelCol: String
    Definition Classes
    HasLabelCol
  75. final def getLeafEstimationBacktracking: ELeavesEstimationStepBacktracking
    Definition Classes
    TrainingParamsTrait
  76. final def getLeafEstimationIterations: Int
    Definition Classes
    TrainingParamsTrait
  77. final def getLeafEstimationMethod: ELeavesEstimation
    Definition Classes
    TrainingParamsTrait
  78. final def getLearningRate: Float
    Definition Classes
    TrainingParamsTrait
  79. final def getLoggingLevel: ELoggingLevel
    Definition Classes
    TrainingParamsTrait
  80. final def getLossFunction: String
    Definition Classes
    TrainingParamsTrait
  81. final def getMetricPeriod: Int
    Definition Classes
    TrainingParamsTrait
  82. final def getModelShrinkMode: EModelShrinkMode
    Definition Classes
    TrainingParamsTrait
  83. final def getModelShrinkRate: Float
    Definition Classes
    TrainingParamsTrait
  84. final def getMvsReg: Float
    Definition Classes
    TrainingParamsTrait
  85. final def getNanMode: ENanMode
    Definition Classes
    QuantizationParamsTrait
  86. final def getOdPval: Float
    Definition Classes
    TrainingParamsTrait
  87. final def getOdType: EOverfittingDetectorType
    Definition Classes
    TrainingParamsTrait
  88. final def getOdWait: Int
    Definition Classes
    TrainingParamsTrait
  89. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  90. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  91. final def getPenaltiesCoefficient: Float
    Definition Classes
    TrainingParamsTrait
  92. final def getPerFloatFeatureQuantizaton: Array[String]
    Definition Classes
    QuantizationParamsTrait
  93. final def getPerObjectFeaturePenaltiesList: Array[Double]
    Definition Classes
    TrainingParamsTrait
  94. final def getPerObjectFeaturePenaltiesMap: LinkedHashMap[String, Float]
    Definition Classes
    TrainingParamsTrait
  95. final def getPredictionCol: String
    Definition Classes
    HasPredictionCol
  96. final def getRandomSeed: Int
    Definition Classes
    TrainingParamsTrait
  97. final def getRandomStrength: Float
    Definition Classes
    TrainingParamsTrait
  98. final def getRsm: Float
    Definition Classes
    TrainingParamsTrait
  99. final def getSamplingFrequency: ESamplingFrequency
    Definition Classes
    TrainingParamsTrait
  100. final def getSamplingUnit: ESamplingUnit
    Definition Classes
    TrainingParamsTrait
  101. final def getSaveSnapshot: Boolean
    Definition Classes
    TrainingParamsTrait
  102. final def getScoreFunction: EScoreFunction
    Definition Classes
    TrainingParamsTrait
  103. final def getSnapshotFile: String
    Definition Classes
    TrainingParamsTrait
  104. final def getSnapshotInterval: Duration
    Definition Classes
    TrainingParamsTrait
  105. final def getSparkPartitionCount: Int
    Definition Classes
    TrainingParamsTrait
  106. final def getSubsample: Float
    Definition Classes
    TrainingParamsTrait
  107. final def getThreadCount: Int
    Definition Classes
    ThreadCountParams
  108. final def getTrainDir: String
    Definition Classes
    TrainingParamsTrait
  109. final def getUseBestModel: Boolean
    Definition Classes
    TrainingParamsTrait
  110. final def getWeightCol: String
    Definition Classes
    HasWeightCol
  111. final def getWorkerInitializationTimeout: Duration
    Definition Classes
    TrainingParamsTrait
  112. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  113. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  114. final val hasTime: BooleanParam
    Definition Classes
    TrainingParamsTrait
  115. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  116. final val ignoredFeaturesIndices: IntArrayParam
    Definition Classes
    IgnoredFeaturesParams
  117. final val ignoredFeaturesNames: StringArrayParam
    Definition Classes
    IgnoredFeaturesParams
  118. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  119. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  120. final val inputBorders: Param[String]
    Definition Classes
    QuantizationParamsTrait
  121. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  122. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  123. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  124. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  125. final val iterations: IntParam
    Definition Classes
    TrainingParamsTrait
  126. final val l2LeafReg: FloatParam
    Definition Classes
    TrainingParamsTrait
  127. final val labelCol: Param[String]
    Definition Classes
    HasLabelCol
  128. final val leafEstimationBacktracking: EnumParam[ELeavesEstimationStepBacktracking]
    Definition Classes
    TrainingParamsTrait
  129. final val leafEstimationIterations: IntParam
    Definition Classes
    TrainingParamsTrait
  130. final val leafEstimationMethod: EnumParam[ELeavesEstimation]
    Definition Classes
    TrainingParamsTrait
  131. final val learningRate: FloatParam
    Definition Classes
    TrainingParamsTrait
  132. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  133. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  134. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  135. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  136. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  137. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  138. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  139. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  140. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  141. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  142. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  143. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  144. final val loggingLevel: EnumParam[ELoggingLevel]
    Definition Classes
    TrainingParamsTrait
  145. final val lossFunction: Param[String]
    Definition Classes
    TrainingParamsTrait
  146. final val metricPeriod: IntParam
    Definition Classes
    TrainingParamsTrait
  147. final val modelShrinkMode: EnumParam[EModelShrinkMode]
    Definition Classes
    TrainingParamsTrait
  148. final val modelShrinkRate: FloatParam
    Definition Classes
    TrainingParamsTrait
  149. final val mvsReg: FloatParam
    Definition Classes
    TrainingParamsTrait
  150. final val nanMode: EnumParam[ENanMode]
    Definition Classes
    QuantizationParamsTrait
  151. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  152. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  153. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  154. final val odPval: FloatParam
    Definition Classes
    TrainingParamsTrait
  155. final val odType: EnumParam[EOverfittingDetectorType]
    Definition Classes
    TrainingParamsTrait
  156. final val odWait: IntParam
    Definition Classes
    TrainingParamsTrait
  157. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  158. final val penaltiesCoefficient: FloatParam
    Definition Classes
    TrainingParamsTrait
  159. final val perFloatFeatureQuantizaton: StringArrayParam
    Definition Classes
    QuantizationParamsTrait
  160. final val perObjectFeaturePenaltiesList: DoubleArrayParam
    Definition Classes
    TrainingParamsTrait
  161. final val perObjectFeaturePenaltiesMap: OrderedStringMapParam[Float]
    Definition Classes
    TrainingParamsTrait
  162. final val predictionCol: Param[String]
    Definition Classes
    HasPredictionCol
  163. def preprocessBeforeTraining(quantizedTrainPool: Pool, quantizedEvalPools: Array[Pool]): (Pool, Array[Pool], JObject)

    override in descendants if necessary

    override in descendants if necessary

    returns

    (preprocessedTrainPool, preprocessedEvalPools, catBoostJsonParams)

    Attributes
    protected
    Definition Classes
    CatBoostPredictorTrait
  164. final val randomSeed: IntParam
    Definition Classes
    TrainingParamsTrait
  165. final val randomStrength: FloatParam
    Definition Classes
    TrainingParamsTrait
  166. final val rsm: FloatParam
    Definition Classes
    TrainingParamsTrait
  167. final val samplingFrequency: EnumParam[ESamplingFrequency]
    Definition Classes
    TrainingParamsTrait
  168. final val samplingUnit: EnumParam[ESamplingUnit]
    Definition Classes
    TrainingParamsTrait
  169. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  170. final val saveSnapshot: BooleanParam
    Definition Classes
    TrainingParamsTrait
  171. final val scoreFunction: EnumParam[EScoreFunction]
    Definition Classes
    TrainingParamsTrait
  172. final def set(paramPair: ParamPair[_]): CatBoostRegressor.this.type
    Attributes
    protected
    Definition Classes
    Params
  173. final def set(param: String, value: Any): CatBoostRegressor.this.type
    Attributes
    protected
    Definition Classes
    Params
  174. final def set[T](param: Param[T], value: T): CatBoostRegressor.this.type
    Definition Classes
    Params
  175. final def setAllowConstLabel(value: Boolean): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  176. final def setAllowWritingFiles(value: Boolean): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  177. final def setApproxOnFullHistory(value: Boolean): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  178. final def setBaggingTemperature(value: Float): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  179. final def setBestModelMinTrees(value: Int): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  180. final def setBootstrapType(value: EBootstrapType): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  181. final def setBorderCount(value: Int): CatBoostRegressor.this.type
    Definition Classes
    QuantizationParamsTrait
  182. final def setCustomMetric(value: Array[String]): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  183. final def setDefault(paramPairs: ParamPair[_]*): CatBoostRegressor.this.type
    Attributes
    protected
    Definition Classes
    Params
  184. final def setDefault[T](param: Param[T], value: T): CatBoostRegressor.this.type
    Attributes
    protected
    Definition Classes
    Params
  185. final def setDepth(value: Int): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  186. final def setDiffusionTemperature(value: Float): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  187. final def setEarlyStoppingRounds(value: Int): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  188. final def setEvalMetric(value: String): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  189. final def setFeatureBorderType(value: EBorderSelectionType): CatBoostRegressor.this.type
    Definition Classes
    QuantizationParamsTrait
  190. final def setFeatureWeightsList(value: Array[Double]): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  191. final def setFeatureWeightsMap(value: LinkedHashMap[String, Float]): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  192. def setFeaturesCol(value: String): CatBoostRegressor
    Definition Classes
    Predictor
  193. final def setFirstFeatureUsePenaltiesList(value: Array[Double]): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  194. final def setFirstFeatureUsePenaltiesMap(value: LinkedHashMap[String, Float]): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  195. final def setFoldLenMultiplier(value: Float): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  196. final def setFoldPermutationBlock(value: Int): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  197. final def setHasTime(value: Boolean): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  198. final def setIgnoredFeaturesIndices(value: Array[Int]): CatBoostRegressor.this.type
    Definition Classes
    IgnoredFeaturesParams
  199. final def setIgnoredFeaturesNames(value: Array[String]): CatBoostRegressor.this.type
    Definition Classes
    IgnoredFeaturesParams
  200. final def setInputBorders(value: String): CatBoostRegressor.this.type
    Definition Classes
    QuantizationParamsTrait
  201. final def setIterations(value: Int): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  202. final def setL2LeafReg(value: Float): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  203. def setLabelCol(value: String): CatBoostRegressor
    Definition Classes
    Predictor
  204. final def setLeafEstimationBacktracking(value: ELeavesEstimationStepBacktracking): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  205. final def setLeafEstimationIterations(value: Int): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  206. final def setLeafEstimationMethod(value: ELeavesEstimation): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  207. final def setLearningRate(value: Float): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  208. final def setLoggingLevel(value: ELoggingLevel): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  209. final def setLossFunction(value: String): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  210. final def setMetricPeriod(value: Int): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  211. final def setModelShrinkMode(value: EModelShrinkMode): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  212. final def setModelShrinkRate(value: Float): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  213. final def setMvsReg(value: Float): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  214. final def setNanMode(value: ENanMode): CatBoostRegressor.this.type
    Definition Classes
    QuantizationParamsTrait
  215. final def setOdPval(value: Float): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  216. final def setOdType(value: EOverfittingDetectorType): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  217. final def setOdWait(value: Int): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  218. final def setPenaltiesCoefficient(value: Float): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  219. final def setPerFloatFeatureQuantizaton(value: Array[String]): CatBoostRegressor.this.type
    Definition Classes
    QuantizationParamsTrait
  220. final def setPerObjectFeaturePenaltiesList(value: Array[Double]): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  221. final def setPerObjectFeaturePenaltiesMap(value: LinkedHashMap[String, Float]): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  222. def setPredictionCol(value: String): CatBoostRegressor
    Definition Classes
    Predictor
  223. final def setRandomSeed(value: Int): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  224. final def setRandomStrength(value: Float): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  225. final def setRsm(value: Float): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  226. final def setSamplingFrequency(value: ESamplingFrequency): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  227. final def setSamplingUnit(value: ESamplingUnit): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  228. final def setSaveSnapshot(value: Boolean): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  229. final def setScoreFunction(value: EScoreFunction): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  230. final def setSnapshotFile(value: String): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  231. final def setSnapshotInterval(value: Duration): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  232. final def setSparkPartitionCount(value: Int): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  233. final def setSubsample(value: Float): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  234. final def setThreadCount(value: Int): CatBoostRegressor.this.type
    Definition Classes
    ThreadCountParams
  235. final def setTrainDir(value: String): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  236. final def setUseBestModel(value: Boolean): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  237. final def setWorkerInitializationTimeout(value: Duration): CatBoostRegressor.this.type
    Definition Classes
    TrainingParamsTrait
  238. final val snapshotFile: Param[String]
    Definition Classes
    TrainingParamsTrait
  239. final val snapshotInterval: DurationParam
    Definition Classes
    TrainingParamsTrait
  240. final val sparkPartitionCount: IntParam
    Definition Classes
    TrainingParamsTrait
  241. final val subsample: FloatParam
    Definition Classes
    TrainingParamsTrait
  242. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  243. final val threadCount: IntParam
    Definition Classes
    ThreadCountParams
  244. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  245. def train(dataset: Dataset[_]): CatBoostRegressionModel
    Attributes
    protected
    Definition Classes
    CatBoostPredictorTrait → Predictor
  246. final val trainDir: Param[String]
    Definition Classes
    TrainingParamsTrait
  247. def transformSchema(schema: StructType): StructType
    Definition Classes
    Predictor → PipelineStage
  248. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  249. val uid: String
    Definition Classes
    CatBoostRegressor → Identifiable
  250. final val useBestModel: BooleanParam
    Definition Classes
    TrainingParamsTrait
  251. def validateAndTransformSchema(schema: StructType, fitting: Boolean, featuresDataType: DataType): StructType
    Attributes
    protected
    Definition Classes
    PredictorParams
  252. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  253. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  254. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  255. final val weightCol: Param[String]
    Definition Classes
    HasWeightCol
  256. final val workerInitializationTimeout: DurationParam
    Definition Classes
    TrainingParamsTrait
  257. def write: MLWriter
    Definition Classes
    DefaultParamsWritable → MLWritable

Inherited from RegressorTrainingParamsTrait

Inherited from TrainingParamsTrait

Inherited from QuantizationParamsTrait

Inherited from ThreadCountParams

Inherited from IgnoredFeaturesParams

Inherited from CatBoostPredictorTrait[CatBoostRegressor, CatBoostRegressionModel]

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from DatasetParamsTrait

Inherited from HasWeightCol

Inherited from CatBoostRegressorBase[Vector, CatBoostRegressor, CatBoostRegressionModel]

Inherited from Regressor[Vector, CatBoostRegressor, CatBoostRegressionModel]

Inherited from Predictor[Vector, CatBoostRegressor, CatBoostRegressionModel]

Inherited from PredictorParams

Inherited from HasPredictionCol

Inherited from HasFeaturesCol

Inherited from HasLabelCol

Inherited from Estimator[CatBoostRegressionModel]

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