object CtrFeatures
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- def addCtrProviderToModel(model: TFullModel, ctrsContext: CtrsContext, quantizedTrainPool: Pool, quantizedEvalPools: Array[Pool]): TFullModel
- def addCtrsAsEstimated(quantizedTrainPool: Pool, quantizedEvalPools: Array[Pool], updatedCatBoostJsonParams: JObject, oneHotMaxSize: Int, classTargetPreprocessor: Option[TClassTargetPreprocessor], serializedLabelConverter: TVector_i8): (Pool, Array[Pool], CtrsContext)
- returns
(trainPoolWithEstimatedFeatures, evalPoolsWithEstimatedFeatures, ctrsContext)
- Note
if repartitioning is applied to result pools CtrsContext will no longer work with them
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- def downloadSubsetOfQuantizedFeatures(quantizedTrainPool: Pool, quantizedEvalPools: Array[Pool], quantizedFeaturesIndices: QuantizedFeaturesIndices, selectedFlatFeaturesIndices: Set[Int], localExecutor: TLocalExecutor): (TQuantizedObjectsDataProviderPtr, TVector_TQuantizedObjectsDataProviderPtr)
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- def getCatFeatureFlatIndicesForCtrs(pool: Pool, oneHotMaxSize: Int): Array[Int]
- returns
array of flat feature indices
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- def getDatasetWithIdsAndIds(df: DataFrame): (DataFrame, Array[Long])
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- def getPreprocessedLearnTarget(pool: Pool, classTargetPreprocessor: Option[TClassTargetPreprocessor]): TVector_float
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- def uploadAndMerge(spark: SparkSession, schema: StructType, aggregateData: DataFrame, ids: Array[Long], estimatedData: TQuantizedObjectsDataProviderPtr): DataFrame
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- Deprecated
(Since version 9)