class CatBoostClassifier extends ProbabilisticClassifier[Vector, CatBoostClassifier, CatBoostClassificationModel] with CatBoostPredictorTrait[CatBoostClassifier, CatBoostClassificationModel] with ClassifierTrainingParamsTrait
Class to train CatBoostClassificationModel
The default optimized loss function depends on various conditions:
Logloss— The label column has only two different values or the targetBorder parameter is specified.MultiClass— The label column has more than two different values and the targetBorder parameter is not specified.
Examples
Binary classification.
val spark = SparkSession.builder() .master("local[*]") .appName("ClassifierTest") .getOrCreate(); val srcDataSchema = Seq( StructField("features", SQLDataTypes.VectorType), StructField("label", StringType) ) val trainData = Seq( Row(Vectors.dense(0.1, 0.2, 0.11), "0"), Row(Vectors.dense(0.97, 0.82, 0.33), "1"), Row(Vectors.dense(0.13, 0.22, 0.23), "1"), Row(Vectors.dense(0.8, 0.62, 0.0), "0") ) 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), "1"), Row(Vectors.dense(0.11, 0.1, 0.21), "0"), Row(Vectors.dense(0.77, 0.0, 0.0), "1") ) val evalDf = spark.createDataFrame(spark.sparkContext.parallelize(evalData), StructType(srcDataSchema)) val evalPool = new Pool(evalDf) val classifier = new CatBoostClassifier val model = classifier.fit(trainPool, Array[Pool](evalPool)) val predictions = model.transform(evalPool.data) predictions.show()
Multiclassification.
val spark = SparkSession.builder() .master("local[*]") .appName("ClassifierTest") .getOrCreate(); val srcDataSchema = Seq( StructField("features", SQLDataTypes.VectorType), StructField("label", StringType) ) val trainData = Seq( Row(Vectors.dense(0.1, 0.2, 0.11), "1"), Row(Vectors.dense(0.97, 0.82, 0.33), "2"), Row(Vectors.dense(0.13, 0.22, 0.23), "1"), Row(Vectors.dense(0.8, 0.62, 0.0), "0") ) 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), "2"), Row(Vectors.dense(0.11, 0.1, 0.21), "0"), Row(Vectors.dense(0.77, 0.0, 0.0), "1") ) val evalDf = spark.createDataFrame(spark.sparkContext.parallelize(evalData), StructType(srcDataSchema)) val evalPool = new Pool(evalDf) val classifier = new CatBoostClassifier val model = classifier.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 classifier = new CatBoostClassifier().setIterations(100) val path = "/home/user/catboost_classifiers/classifier0" classifier.write.save(path)
Load:
val path = "/home/user/catboost_classifiers/classifier0" val classifier = CatBoostClassifier.load(path) val trainPool : Pool = ... init Pool ... val model = classifier.fit(trainPool)
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- def fit(trainPool: Pool, evalPools: Array[Pool] = Array[Pool]()): CatBoostClassificationModel
Additional variant of
fitmethod 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
fitmethod 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.
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trained model
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- def preprocessBeforeTraining(quantizedTrainPool: Pool, quantizedEvalPools: Array[Pool]): (Pool, Array[Pool], CatBoostTrainingContext)
override in descendants if necessary
override in descendants if necessary
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- final def setClassWeightsMap(value: LinkedHashMap[String, Double]): CatBoostClassifier.this.type
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- final def setClassesCount(value: Int): CatBoostClassifier.this.type
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- TrainingParamsTrait
- final def setFeatureBorderType(value: EBorderSelectionType): CatBoostClassifier.this.type
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- QuantizationParamsTrait
- final def setFeatureWeightsList(value: Array[Double]): CatBoostClassifier.this.type
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- TrainingParamsTrait
- final def setFeatureWeightsMap(value: LinkedHashMap[String, Double]): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- def setFeaturesCol(value: String): CatBoostClassifier
- Definition Classes
- Predictor
- final def setFirstFeatureUsePenaltiesList(value: Array[Double]): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setFirstFeatureUsePenaltiesMap(value: LinkedHashMap[String, Double]): CatBoostClassifier.this.type
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- TrainingParamsTrait
- final def setFoldLenMultiplier(value: Float): CatBoostClassifier.this.type
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- TrainingParamsTrait
- final def setFoldPermutationBlock(value: Int): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setHasTime(value: Boolean): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setIgnoredFeaturesIndices(value: Array[Int]): CatBoostClassifier.this.type
- Definition Classes
- IgnoredFeaturesParams
- final def setIgnoredFeaturesNames(value: Array[String]): CatBoostClassifier.this.type
- Definition Classes
- IgnoredFeaturesParams
- final def setInputBorders(value: String): CatBoostClassifier.this.type
- Definition Classes
- QuantizationParamsTrait
- final def setIterations(value: Int): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setL2LeafReg(value: Float): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- def setLabelCol(value: String): CatBoostClassifier
- Definition Classes
- Predictor
- final def setLeafEstimationBacktracking(value: ELeavesEstimationStepBacktracking): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setLeafEstimationIterations(value: Int): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setLeafEstimationMethod(value: ELeavesEstimation): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setLearningRate(value: Float): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setLoggingLevel(value: ELoggingLevel): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setLossFunction(value: String): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setMetricPeriod(value: Int): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setModelShrinkMode(value: EModelShrinkMode): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setModelShrinkRate(value: Float): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setMvsReg(value: Float): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setNanMode(value: ENanMode): CatBoostClassifier.this.type
- Definition Classes
- QuantizationParamsTrait
- final def setOdPval(value: Float): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setOdType(value: EOverfittingDetectorType): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setOdWait(value: Int): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setOneHotMaxSize(value: Int): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setPenaltiesCoefficient(value: Float): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setPerFloatFeatureQuantizaton(value: Array[String]): CatBoostClassifier.this.type
- Definition Classes
- QuantizationParamsTrait
- final def setPerObjectFeaturePenaltiesList(value: Array[Double]): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setPerObjectFeaturePenaltiesMap(value: LinkedHashMap[String, Double]): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- def setPredictionCol(value: String): CatBoostClassifier
- Definition Classes
- Predictor
- def setProbabilityCol(value: String): CatBoostClassifier
- Definition Classes
- ProbabilisticClassifier
- final def setRandomSeed(value: Int): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setRandomStrength(value: Float): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- def setRawPredictionCol(value: String): CatBoostClassifier
- Definition Classes
- Classifier
- final def setRsm(value: Float): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setSamplingFrequency(value: ESamplingFrequency): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setSamplingUnit(value: ESamplingUnit): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setSaveSnapshot(value: Boolean): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setScalePosWeight(value: Float): CatBoostClassifier.this.type
- Definition Classes
- ClassifierTrainingParamsTrait
- final def setScoreFunction(value: EScoreFunction): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setSnapshotFile(value: String): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setSnapshotInterval(value: Duration): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setSparkPartitionCount(value: Int): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setSubsample(value: Float): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setTargetBorder(value: Float): CatBoostClassifier.this.type
- Definition Classes
- ClassifierTrainingParamsTrait
- final def setThreadCount(value: Int): CatBoostClassifier.this.type
- Definition Classes
- ThreadCountParams
- def setThresholds(value: Array[Double]): CatBoostClassifier
- Definition Classes
- ProbabilisticClassifier
- final def setTrainDir(value: String): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setTrainingDriverListeningPort(value: Int): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setUseBestModel(value: Boolean): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setWorkerInitializationTimeout(value: Duration): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setWorkerListeningPort(value: Int): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final def setWorkerMaxFailures(value: Int): CatBoostClassifier.this.type
- Definition Classes
- TrainingParamsTrait
- final val snapshotFile: Param[String]
- Definition Classes
- TrainingParamsTrait
- final val snapshotInterval: DurationParam
- Definition Classes
- TrainingParamsTrait
- final val sparkPartitionCount: IntParam
- Definition Classes
- TrainingParamsTrait
- final val subsample: FloatParam
- Definition Classes
- TrainingParamsTrait
- final def synchronized[T0](arg0: => T0): T0
- Definition Classes
- AnyRef
- final val targetBorder: FloatParam
- Definition Classes
- ClassifierTrainingParamsTrait
- final val threadCount: IntParam
- Definition Classes
- ThreadCountParams
- val thresholds: DoubleArrayParam
- Definition Classes
- HasThresholds
- def toString(): String
- Definition Classes
- Identifiable → AnyRef → Any
- def train(dataset: Dataset[_]): CatBoostClassificationModel
- Attributes
- protected
- Definition Classes
- CatBoostPredictorTrait → Predictor
- final val trainDir: Param[String]
- Definition Classes
- TrainingParamsTrait
- final val trainingDriverListeningPort: IntParam
- Definition Classes
- TrainingParamsTrait
- def transformSchema(schema: StructType): StructType
- Definition Classes
- Predictor → PipelineStage
- def transformSchema(schema: StructType, logging: Boolean): StructType
- Attributes
- protected
- Definition Classes
- PipelineStage
- Annotations
- @DeveloperApi()
- val uid: String
- Definition Classes
- CatBoostClassifier → Identifiable
- final val useBestModel: BooleanParam
- Definition Classes
- TrainingParamsTrait
- def validateAndTransformSchema(schema: StructType, fitting: Boolean, featuresDataType: DataType): StructType
- Attributes
- protected
- Definition Classes
- ProbabilisticClassifierParams → ClassifierParams → PredictorParams
- final def wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long, arg1: Int): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException]) @native()
- final val weightCol: Param[String]
- Definition Classes
- HasWeightCol
- final val workerInitializationTimeout: DurationParam
- Definition Classes
- TrainingParamsTrait
- final val workerListeningPort: IntParam
- Definition Classes
- TrainingParamsTrait
- final val workerMaxFailures: IntParam
- Definition Classes
- TrainingParamsTrait
- def write: MLWriter
- Definition Classes
- DefaultParamsWritable → MLWritable