trait LightGBMBase[TrainedModel <: Model[TrainedModel]] extends Estimator[TrainedModel] with LightGBMParams with HasFeaturesCol with HasLabelCol with LightGBMPerformance with SynapseMLLogging
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- LightGBMBase
- SynapseMLLogging
- LightGBMPerformance
- HasLabelCol
- HasFeaturesCol
- LightGBMParams
- LightGBMCategoricalParams
- LightGBMSeedParams
- LightGBMObjectiveParams
- LightGBMPredictionParams
- LightGBMDartParams
- LightGBMDatasetParams
- LightGBMLearnerParams
- LightGBMBinParams
- LightGBMFractionParams
- LightGBMSlotParams
- LightGBMExecutionParams
- HasInitScoreCol
- HasValidationIndicatorCol
- HasWeightCol
- DefaultParamsWritable
- MLWritable
- Wrappable
- DotnetWrappable
- RWrappable
- PythonWrappable
- BaseWrappable
- Estimator
- PipelineStage
- Logging
- Params
- Serializable
- Serializable
- Identifiable
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Abstract Value Members
-
abstract
def
copy(extra: ParamMap): Estimator[TrainedModel]
- Definition Classes
- Estimator → PipelineStage → Params
-
abstract
def
fit(dataset: Dataset[_]): TrainedModel
- Definition Classes
- Estimator
- Annotations
- @Since( "2.0.0" )
-
abstract
def
getModel(trainParams: BaseTrainParams, lightGBMBooster: LightGBMBooster): TrainedModel
Gets the trained model given the train parameters and booster.
Gets the trained model given the train parameters and booster.
- returns
trained model.
- Attributes
- protected
-
abstract
def
getTrainParams(numTasks: Int, featuresSchema: StructField, numTasksPerExec: Int): BaseTrainParams
Gets the training parameters.
Gets the training parameters.
- numTasks
The total number of tasks.
- featuresSchema
The features column schema.
- numTasksPerExec
The number of tasks per executor.
- returns
train parameters.
- Attributes
- protected
-
abstract
def
stringFromTrainedModel(model: TrainedModel): String
- Attributes
- protected
-
abstract
def
transformSchema(schema: StructType): StructType
- Definition Classes
- PipelineStage
-
abstract
val
uid: String
- Definition Classes
- SynapseMLLogging
Concrete Value Members
-
final
def
!=(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
-
final
def
##(): Int
- Definition Classes
- AnyRef → Any
-
final
def
$[T](param: Param[T]): T
- Attributes
- protected
- Definition Classes
- Params
-
final
def
==(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
-
def
addCustomTrainParams(params: BaseTrainParams, dataset: Dataset[_]): BaseTrainParams
- Attributes
- protected
- def afterTrainBatch(batchIndex: Int, dataset: Dataset[_], model: TrainedModel): Unit
-
final
def
asInstanceOf[T0]: T0
- Definition Classes
- Any
-
val
baggingFraction: DoubleParam
- Definition Classes
- LightGBMFractionParams
-
val
baggingFreq: IntParam
- Definition Classes
- LightGBMParams
-
val
baggingSeed: IntParam
- Definition Classes
- LightGBMSeedParams
- def beforeTrainBatch(batchIndex: Int, dataset: Dataset[_], model: Option[TrainedModel]): Unit
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val
binSampleCount: IntParam
- Definition Classes
- LightGBMBinParams
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val
boostFromAverage: BooleanParam
- Definition Classes
- LightGBMParams
-
val
boostingType: Param[String]
- Definition Classes
- LightGBMParams
-
def
calculateColumnStatistics(dataframe: DataFrame, measures: InstrumentationMeasures): (Int, Int)
Extract column counts from the dataset.
Extract column counts from the dataset.
- dataframe
The dataset to train on.
- returns
The number of feature columns and initial score classes
- Attributes
- protected
-
def
calculateRowStatistics(dataframe: DataFrame, trainingParams: BaseTrainParams, numCols: Int, measures: InstrumentationMeasures): (Array[Row], Array[Long])
Inner train method for LightGBM learners.
Inner train method for LightGBM learners. Calculates the number of workers, creates a driver thread, and runs mapPartitions on the dataset.
- dataframe
The dataset to train on.
- trainingParams
The training parameters.
- numCols
The number of feature columns.
- returns
The serialized Dataset reference and an array of partition counts.
- Attributes
- protected
-
def
castColumns(dataset: Dataset[_], trainingCols: Array[(String, Seq[DataType])]): DataFrame
- Attributes
- protected
-
val
catSmooth: DoubleParam
- Definition Classes
- LightGBMCategoricalParams
-
val
categoricalSlotIndexes: IntArrayParam
- Definition Classes
- LightGBMSlotParams
-
val
categoricalSlotNames: StringArrayParam
- Definition Classes
- LightGBMSlotParams
-
val
catl2: DoubleParam
- Definition Classes
- LightGBMCategoricalParams
-
val
chunkSize: IntParam
- Definition Classes
- LightGBMExecutionParams
-
lazy val
classNameHelper: String
- Attributes
- protected
- Definition Classes
- BaseWrappable
-
final
def
clear(param: Param[_]): LightGBMBase.this.type
- Definition Classes
- Params
-
def
clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws( ... ) @native()
-
def
companionModelClassName: String
- Attributes
- protected
- Definition Classes
- BaseWrappable
-
def
copyValues[T <: Params](to: T, extra: ParamMap): T
- Attributes
- protected
- Definition Classes
- Params
-
lazy val
copyrightLines: String
- Attributes
- protected
- Definition Classes
- BaseWrappable
-
val
dataRandomSeed: IntParam
- Definition Classes
- LightGBMSeedParams
-
final
def
defaultCopy[T <: Params](extra: ParamMap): T
- Attributes
- protected
- Definition Classes
- Params
-
val
defaultListenPort: IntParam
- Definition Classes
- LightGBMExecutionParams
-
val
delegate: Option[LightGBMDelegate]
- Definition Classes
- LightGBMParams
-
val
deterministic: BooleanParam
- Definition Classes
- LightGBMSeedParams
-
def
dotnetAdditionalMethods: String
- Definition Classes
- DotnetWrappable
-
def
dotnetClass(): String
- Attributes
- protected
- Definition Classes
- DotnetWrappable
-
lazy val
dotnetClassName: String
- Attributes
- protected
- Definition Classes
- DotnetWrappable
-
lazy val
dotnetClassNameString: String
- Attributes
- protected
- Definition Classes
- DotnetWrappable
-
lazy val
dotnetClassWrapperName: String
- Attributes
- protected
- Definition Classes
- DotnetWrappable
-
lazy val
dotnetCopyrightLines: String
- Attributes
- protected
- Definition Classes
- DotnetWrappable
-
def
dotnetExtraEstimatorImports: String
- Attributes
- protected
- Definition Classes
- DotnetWrappable
-
def
dotnetExtraMethods: String
- Attributes
- protected
- Definition Classes
- DotnetWrappable
-
lazy val
dotnetInternalWrapper: Boolean
- Attributes
- protected
- Definition Classes
- DotnetWrappable
-
def
dotnetMLReadWriteMethods: String
- Attributes
- protected
- Definition Classes
- DotnetWrappable
-
lazy val
dotnetNamespace: String
- Attributes
- protected
- Definition Classes
- DotnetWrappable
-
lazy val
dotnetObjectBaseClass: String
- Attributes
- protected
- Definition Classes
- DotnetWrappable
-
def
dotnetParamGetter(p: Param[_]): String
- Attributes
- protected
- Definition Classes
- DotnetWrappable
-
def
dotnetParamGetters: String
- Attributes
- protected
- Definition Classes
- DotnetWrappable
-
def
dotnetParamSetter(p: Param[_]): String
- Attributes
- protected
- Definition Classes
- DotnetWrappable
-
def
dotnetParamSetters: String
- Attributes
- protected
- Definition Classes
- DotnetWrappable
-
def
dotnetWrapAsTypeMethod: String
- Attributes
- protected
- Definition Classes
- DotnetWrappable
-
val
driverListenPort: IntParam
- Definition Classes
- LightGBMExecutionParams
-
val
dropRate: DoubleParam
- Definition Classes
- LightGBMDartParams
-
val
dropSeed: IntParam
- Definition Classes
- LightGBMSeedParams
-
val
earlyStoppingRound: IntParam
- Definition Classes
- LightGBMLearnerParams
-
final
def
eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
-
def
equals(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
-
def
executePartitionTasks(ctx: TrainingContext, dataframe: DataFrame, measures: InstrumentationMeasures): LightGBMBooster
- Attributes
- protected
-
def
executeTraining(dataframe: DataFrame, validationData: Option[Broadcast[Array[Row]]], broadcastedSampleData: Option[Broadcast[Array[Row]]], partitionCounts: Option[Array[Long]], trainParams: BaseTrainParams, numCols: Int, numInitValueClasses: Int, batchIndex: Int, numTasks: Int, numTasksPerExecutor: Int, measures: InstrumentationMeasures): TrainedModel
Run a parallel job via map partitions to initialize the native library and network, translate the data to the LightGBM in-memory representation and train the models.
Run a parallel job via map partitions to initialize the native library and network, translate the data to the LightGBM in-memory representation and train the models.
- dataframe
The dataset to train on.
- validationData
The dataset to use as validation. (optional)
- broadcastedSampleData
Sample data to use for streaming mode Dataset creation (optional).
- partitionCounts
The count per partition for streaming mode (optional).
- trainParams
Training parameters.
- numCols
Number of columns.
- numInitValueClasses
Number of classes for initial values (used only for multiclass).
- batchIndex
In running in batch training mode, gets the batch number.
- numTasks
Number of tasks/partitions.
- numTasksPerExecutor
Number of tasks per executor.
- measures
Instrumentation measures to populate.
- returns
The LightGBM Model from the trained LightGBM Booster.
- Attributes
- protected
-
val
executionMode: Param[String]
- Definition Classes
- LightGBMExecutionParams
-
def
explainParam(param: Param[_]): String
- Definition Classes
- Params
-
def
explainParams(): String
- Definition Classes
- Params
-
val
extraSeed: IntParam
- Definition Classes
- LightGBMSeedParams
-
final
def
extractParamMap(): ParamMap
- Definition Classes
- Params
-
final
def
extractParamMap(extra: ParamMap): ParamMap
- Definition Classes
- Params
-
val
featureFraction: DoubleParam
- Definition Classes
- LightGBMFractionParams
-
val
featureFractionByNode: DoubleParam
- Definition Classes
- LightGBMFractionParams
-
val
featureFractionSeed: IntParam
- Definition Classes
- LightGBMSeedParams
-
final
val
featuresCol: Param[String]
- Definition Classes
- HasFeaturesCol
-
val
featuresShapCol: Param[String]
- Definition Classes
- LightGBMPredictionParams
-
def
finalize(): Unit
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws( classOf[java.lang.Throwable] )
-
def
fit(dataset: Dataset[_], paramMaps: Seq[ParamMap]): Seq[TrainedModel]
- Definition Classes
- Estimator
- Annotations
- @Since( "2.0.0" )
-
def
fit(dataset: Dataset[_], paramMap: ParamMap): TrainedModel
- Definition Classes
- Estimator
- Annotations
- @Since( "2.0.0" )
-
def
fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): TrainedModel
- Definition Classes
- Estimator
- Annotations
- @Since( "2.0.0" ) @varargs()
-
val
fobj: FObjParam
- Definition Classes
- LightGBMObjectiveParams
-
final
def
get[T](param: Param[T]): Option[T]
- Definition Classes
- Params
-
def
getAllPerformanceMeasures: Option[Array[InstrumentationMeasures]]
- Definition Classes
- LightGBMPerformance
-
def
getBaggingFraction: Double
- Definition Classes
- LightGBMFractionParams
-
def
getBaggingFreq: Int
- Definition Classes
- LightGBMParams
-
def
getBaggingSeed: Int
- Definition Classes
- LightGBMSeedParams
-
def
getBinSampleCount: Int
- Definition Classes
- LightGBMBinParams
-
def
getBoostFromAverage: Boolean
- Definition Classes
- LightGBMParams
-
def
getBoostingType: String
- Definition Classes
- LightGBMParams
-
def
getCatSmooth: Double
- Definition Classes
- LightGBMCategoricalParams
-
def
getCategoricalIndexes(featuresSchema: StructField): Array[Int]
Retrieves the categorical indexes in the features column.
Retrieves the categorical indexes in the features column.
- featuresSchema
The schema of the features column
- returns
the categorical indexes in the features column.
- Attributes
- protected
-
def
getCategoricalParams: CategoricalParams
Constructs the CategoricalParams.
Constructs the CategoricalParams.
- returns
CategoricalParams object containing the parameters related to LightGBM categorical features.
- Attributes
- protected
-
def
getCategoricalSlotIndexes: Array[Int]
- Definition Classes
- LightGBMSlotParams
-
def
getCategoricalSlotNames: Array[String]
- Definition Classes
- LightGBMSlotParams
-
def
getCatl2: Double
- Definition Classes
- LightGBMCategoricalParams
-
def
getChunkSize: Int
- Definition Classes
- LightGBMExecutionParams
-
final
def
getClass(): Class[_]
- Definition Classes
- AnyRef → Any
- Annotations
- @native()
-
def
getColumnParams: ColumnParams
Constructs the ColumnParams.
Constructs the ColumnParams.
- returns
ColumnParams object containing the parameters related to LightGBM columns.
- Attributes
- protected
-
def
getDartParams: DartModeParams
Constructs the DartModeParams
Constructs the DartModeParams
- returns
DartModeParams object containing parameters related to dart mode.
- Attributes
- protected
-
def
getDataRandomSeed: Int
- Definition Classes
- LightGBMSeedParams
- def getDatasetCreationParams(categoricalIndexes: Array[Int], numThreads: Int): String
-
def
getDatasetParams: DatasetParams
Constructs the DatasetParams.
Constructs the DatasetParams.
- returns
DatasetParams object containing parameters related to LightGBM Dataset parameters.
- Attributes
- protected
-
final
def
getDefault[T](param: Param[T]): Option[T]
- Definition Classes
- Params
-
def
getDefaultListenPort: Int
- Definition Classes
- LightGBMExecutionParams
-
def
getDelegate: Option[LightGBMDelegate]
- Definition Classes
- LightGBMParams
-
def
getDeterministic: Boolean
- Definition Classes
- LightGBMSeedParams
-
def
getDriverListenPort: Int
- Definition Classes
- LightGBMExecutionParams
-
def
getDropRate: Double
- Definition Classes
- LightGBMDartParams
-
def
getDropSeed: Int
- Definition Classes
- LightGBMSeedParams
-
def
getEarlyStoppingRound: Int
- Definition Classes
- LightGBMLearnerParams
-
def
getExecutionMode: String
- Definition Classes
- LightGBMExecutionParams
-
def
getExecutionParams(numTasksPerExec: Int): ExecutionParams
Constructs the ExecutionParams.
Constructs the ExecutionParams.
- returns
ExecutionParams object containing parameters related to LightGBM execution.
- Attributes
- protected
-
def
getExtraSeed: Int
- Definition Classes
- LightGBMSeedParams
-
def
getFObj: FObjTrait
- Definition Classes
- LightGBMObjectiveParams
-
def
getFeatureFraction: Double
- Definition Classes
- LightGBMFractionParams
-
def
getFeatureFractionByNode: Double
- Definition Classes
- LightGBMFractionParams
-
def
getFeatureFractionSeed: Int
- Definition Classes
- LightGBMSeedParams
-
final
def
getFeaturesCol: String
- Definition Classes
- HasFeaturesCol
-
def
getFeaturesShapCol: String
- Definition Classes
- LightGBMPredictionParams
-
def
getGeneralParams(numTasks: Int, featuresSchema: StructField): GeneralParams
Constructs the GeneralParams.
Constructs the GeneralParams.
- returns
GeneralParams object containing parameters related to general LightGBM parameters.
- Attributes
- protected
-
def
getImprovementTolerance: Double
- Definition Classes
- LightGBMLearnerParams
-
def
getInitScoreCol: String
- Definition Classes
- HasInitScoreCol
-
def
getIsEnableSparse: Boolean
- Definition Classes
- LightGBMDatasetParams
-
def
getIsProvideTrainingMetric: Boolean
- Definition Classes
- LightGBMParams
-
final
def
getLabelCol: String
- Definition Classes
- HasLabelCol
-
def
getLambdaL1: Double
- Definition Classes
- LightGBMParams
-
def
getLambdaL2: Double
- Definition Classes
- LightGBMParams
-
def
getLeafPredictionCol: String
- Definition Classes
- LightGBMPredictionParams
-
def
getLearningRate: Double
- Definition Classes
- LightGBMParams
-
def
getMatrixType: String
- Definition Classes
- LightGBMExecutionParams
-
def
getMaxBin: Int
- Definition Classes
- LightGBMBinParams
-
def
getMaxBinByFeature: Array[Int]
- Definition Classes
- LightGBMParams
-
def
getMaxCatThreshold: Int
- Definition Classes
- LightGBMCategoricalParams
-
def
getMaxCatToOnehot: Int
- Definition Classes
- LightGBMCategoricalParams
-
def
getMaxDeltaStep: Double
- Definition Classes
- LightGBMParams
-
def
getMaxDepth: Int
- Definition Classes
- LightGBMParams
-
def
getMaxDrop: Int
- Definition Classes
- LightGBMDartParams
-
def
getMaxNumClasses: Int
- Definition Classes
- LightGBMParams
-
def
getMaxStreamingOMPThreads: Int
- Definition Classes
- LightGBMExecutionParams
-
def
getMetric: String
- Definition Classes
- LightGBMParams
-
def
getMicroBatchSize: Int
- Definition Classes
- LightGBMExecutionParams
-
def
getMinDataInLeaf: Int
- Definition Classes
- LightGBMParams
-
def
getMinDataPerBin: Int
- Definition Classes
- LightGBMParams
-
def
getMinDataPerGroup: Int
- Definition Classes
- LightGBMCategoricalParams
-
def
getMinGainToSplit: Double
- Definition Classes
- LightGBMParams
-
def
getMinSumHessianInLeaf: Double
- Definition Classes
- LightGBMParams
-
def
getModelString: String
- Definition Classes
- LightGBMParams
-
def
getMonotoneConstraints: Array[Int]
- Definition Classes
- LightGBMLearnerParams
-
def
getMonotoneConstraintsMethod: String
- Definition Classes
- LightGBMLearnerParams
-
def
getMonotonePenalty: Double
- Definition Classes
- LightGBMLearnerParams
-
def
getNegBaggingFraction: Double
- Definition Classes
- LightGBMFractionParams
-
def
getNumBatches: Int
- Definition Classes
- LightGBMExecutionParams
-
def
getNumIterations: Int
- Definition Classes
- LightGBMParams
-
def
getNumLeaves: Int
- Definition Classes
- LightGBMParams
-
def
getNumTasks: Int
- Definition Classes
- LightGBMExecutionParams
-
def
getNumThreads: Int
- Definition Classes
- LightGBMExecutionParams
-
def
getObjective: String
- Definition Classes
- LightGBMObjectiveParams
-
def
getObjectiveParams: ObjectiveParams
Constructs the ObjectiveParams.
Constructs the ObjectiveParams.
- returns
ObjectiveParams object containing parameters related to the objective function.
- Attributes
- protected
-
def
getObjectiveSeed: Int
- Definition Classes
- LightGBMSeedParams
-
def
getOptGroupCol: Option[String]
Optional group column for Ranking, set to None by default.
Optional group column for Ranking, set to None by default.
- returns
None
- Attributes
- protected
-
final
def
getOrDefault[T](param: Param[T]): T
- Definition Classes
- Params
-
def
getOtherRate: Double
- Definition Classes
- LightGBMLearnerParams
-
def
getParallelism: String
- Definition Classes
- LightGBMExecutionParams
-
def
getParam(paramName: String): Param[Any]
- Definition Classes
- Params
-
def
getParamInfo(p: Param[_]): ParamInfo[_]
- Definition Classes
- BaseWrappable
-
def
getPassThroughArgs: String
- Definition Classes
- LightGBMExecutionParams
-
def
getPerformanceMeasures: Option[InstrumentationMeasures]
In the common case of 1 batch, there is only 1 measure, so this is a convenience method.
In the common case of 1 batch, there is only 1 measure, so this is a convenience method.
- Definition Classes
- LightGBMPerformance
-
def
getPosBaggingFraction: Double
- Definition Classes
- LightGBMFractionParams
-
def
getPredictDisableShapeCheck: Boolean
- Definition Classes
- LightGBMPredictionParams
-
def
getRepartitionByGroupingColumn: Boolean
- Definition Classes
- LightGBMExecutionParams
-
def
getSeed: Int
- Definition Classes
- LightGBMSeedParams
-
def
getSeedParams: SeedParams
Constructs the SeedParams.
Constructs the SeedParams.
- returns
SeedParams object containing the parameters related to LightGBM seeds and determinism.
- Attributes
- protected
-
def
getSkipDrop: Double
- Definition Classes
- LightGBMDartParams
-
def
getSlotNames: Array[String]
- Definition Classes
- LightGBMSlotParams
- def getSlotNamesWithMetadata(featuresSchema: StructField): Option[Array[String]]
-
def
getTimeout: Double
- Definition Classes
- LightGBMExecutionParams
-
def
getTopK: Int
- Definition Classes
- LightGBMExecutionParams
-
def
getTopRate: Double
- Definition Classes
- LightGBMLearnerParams
-
def
getTrainingCols: Array[(String, Seq[DataType])]
- Attributes
- protected
-
def
getTrainingContext(dataframe: DataFrame, validationData: Option[Broadcast[Array[Row]]], broadcastedSampleData: Option[Broadcast[Array[Row]]], partitionCounts: Option[Array[Long]], trainParams: BaseTrainParams, numCols: Int, numInitValueClasses: Int, batchIndex: Int, numTasksPerExecutor: Int, networkManager: NetworkManager): TrainingContext
Get the object that holds all relevant context information for the training session.
Get the object that holds all relevant context information for the training session.
- dataframe
The dataset to train on.
- validationData
The dataset to use as validation. (optional)
- broadcastedSampleData
Sample data to use for streaming mode Dataset creation (optional).
- partitionCounts
The count per partition for streaming mode (optional).
- trainParams
Training parameters.
- numCols
Number of columns.
- numInitValueClasses
Number of classes for initial values (used only for multiclass).
- batchIndex
In running in batch training mode, gets the batch number.
- numTasksPerExecutor
Number of tasks per executor.
- networkManager
The network manager.
- returns
The context of the training session.
- Attributes
- protected
-
def
getUniformDrop: Boolean
- Definition Classes
- LightGBMDartParams
-
def
getUseBarrierExecutionMode: Boolean
- Definition Classes
- LightGBMExecutionParams
-
def
getUseMissing: Boolean
- Definition Classes
- LightGBMDatasetParams
-
def
getUseSingleDatasetMode: Boolean
- Definition Classes
- LightGBMExecutionParams
-
def
getValidationIndicatorCol: String
- Definition Classes
- HasValidationIndicatorCol
-
def
getVerbosity: Int
- Definition Classes
- LightGBMParams
-
def
getWeightCol: String
- Definition Classes
- HasWeightCol
-
def
getXGBoostDartMode: Boolean
- Definition Classes
- LightGBMDartParams
-
def
getZeroAsMissing: Boolean
- Definition Classes
- LightGBMDatasetParams
-
final
def
hasDefault[T](param: Param[T]): Boolean
- Definition Classes
- Params
-
def
hasParam(paramName: String): Boolean
- Definition Classes
- Params
-
def
hashCode(): Int
- Definition Classes
- AnyRef → Any
- Annotations
- @native()
-
val
improvementTolerance: DoubleParam
- Definition Classes
- LightGBMLearnerParams
-
def
initPerformanceMeasures(batchCount: Int): Unit
- Attributes
- protected
- Definition Classes
- LightGBMPerformance
-
val
initScoreCol: Param[String]
The name of the initial score column
The name of the initial score column
- Definition Classes
- HasInitScoreCol
-
def
initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
- Attributes
- protected
- Definition Classes
- Logging
-
def
initializeLogIfNecessary(isInterpreter: Boolean): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
final
def
isDefined(param: Param[_]): Boolean
- Definition Classes
- Params
-
val
isEnableSparse: BooleanParam
- Definition Classes
- LightGBMDatasetParams
-
final
def
isInstanceOf[T0]: Boolean
- Definition Classes
- Any
-
val
isProvideTrainingMetric: BooleanParam
- Definition Classes
- LightGBMParams
-
final
def
isSet(param: Param[_]): Boolean
- Definition Classes
- Params
-
def
isTraceEnabled(): Boolean
- Attributes
- protected
- Definition Classes
- Logging
-
final
val
labelCol: Param[String]
- Definition Classes
- HasLabelCol
-
val
lambdaL1: DoubleParam
- Definition Classes
- LightGBMParams
-
val
lambdaL2: DoubleParam
- Definition Classes
- LightGBMParams
-
val
leafPredictionCol: Param[String]
- Definition Classes
- LightGBMPredictionParams
-
val
learningRate: DoubleParam
- Definition Classes
- LightGBMParams
-
def
log: Logger
- Attributes
- protected
- Definition Classes
- Logging
-
def
logBase(info: SynapseMLLogInfo): Unit
- Attributes
- protected
- Definition Classes
- SynapseMLLogging
-
def
logBase(methodName: String, columns: Option[Int]): Unit
- Attributes
- protected
- Definition Classes
- SynapseMLLogging
-
def
logClass(): Unit
- Definition Classes
- SynapseMLLogging
-
def
logDebug(msg: ⇒ String, throwable: Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
logDebug(msg: ⇒ String): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
logError(msg: ⇒ String, throwable: Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
logError(msg: ⇒ String): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
logErrorBase(methodName: String, e: Exception): Unit
- Attributes
- protected
- Definition Classes
- SynapseMLLogging
-
def
logFit[T](f: ⇒ T, columns: Int): T
- Definition Classes
- SynapseMLLogging
-
def
logInfo(msg: ⇒ String, throwable: Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
logInfo(msg: ⇒ String): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
logName: String
- Attributes
- protected
- Definition Classes
- Logging
-
def
logTrace(msg: ⇒ String, throwable: Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
logTrace(msg: ⇒ String): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
logTrain[T](f: ⇒ T, columns: Int): T
- Definition Classes
- SynapseMLLogging
-
def
logTransform[T](f: ⇒ T, columns: Int): T
- Definition Classes
- SynapseMLLogging
-
def
logVerb[T](verb: String, f: ⇒ T, columns: Int = -1): T
- Definition Classes
- SynapseMLLogging
-
def
logWarning(msg: ⇒ String, throwable: Throwable): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
logWarning(msg: ⇒ String): Unit
- Attributes
- protected
- Definition Classes
- Logging
-
def
makeDotnetFile(conf: CodegenConfig): Unit
- Definition Classes
- DotnetWrappable
-
def
makePyFile(conf: CodegenConfig): Unit
- Definition Classes
- PythonWrappable
-
def
makeRFile(conf: CodegenConfig): Unit
- Definition Classes
- RWrappable
-
val
matrixType: Param[String]
- Definition Classes
- LightGBMExecutionParams
-
val
maxBin: IntParam
- Definition Classes
- LightGBMBinParams
-
val
maxBinByFeature: IntArrayParam
- Definition Classes
- LightGBMParams
-
val
maxCatThreshold: IntParam
- Definition Classes
- LightGBMCategoricalParams
-
val
maxCatToOnehot: IntParam
- Definition Classes
- LightGBMCategoricalParams
-
val
maxDeltaStep: DoubleParam
- Definition Classes
- LightGBMParams
-
val
maxDepth: IntParam
- Definition Classes
- LightGBMParams
-
val
maxDrop: IntParam
- Definition Classes
- LightGBMDartParams
-
val
maxNumClasses: IntParam
- Definition Classes
- LightGBMParams
-
val
maxStreamingOMPThreads: IntParam
- Definition Classes
- LightGBMExecutionParams
-
val
metric: Param[String]
- Definition Classes
- LightGBMParams
-
val
microBatchSize: IntParam
- Definition Classes
- LightGBMExecutionParams
-
val
minDataInLeaf: IntParam
- Definition Classes
- LightGBMParams
-
val
minDataPerBin: IntParam
- Definition Classes
- LightGBMParams
-
val
minDataPerGroup: IntParam
- Definition Classes
- LightGBMCategoricalParams
-
val
minGainToSplit: DoubleParam
- Definition Classes
- LightGBMParams
-
val
minSumHessianInLeaf: DoubleParam
- Definition Classes
- LightGBMParams
-
val
modelString: Param[String]
- Definition Classes
- LightGBMParams
-
val
monotoneConstraints: IntArrayParam
- Definition Classes
- LightGBMLearnerParams
-
val
monotoneConstraintsMethod: Param[String]
- Definition Classes
- LightGBMLearnerParams
-
val
monotonePenalty: DoubleParam
- Definition Classes
- LightGBMLearnerParams
-
final
def
ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
-
val
negBaggingFraction: DoubleParam
- Definition Classes
- LightGBMFractionParams
-
final
def
notify(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native()
-
final
def
notifyAll(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native()
-
val
numBatches: IntParam
- Definition Classes
- LightGBMExecutionParams
-
val
numIterations: IntParam
- Definition Classes
- LightGBMParams
-
val
numLeaves: IntParam
- Definition Classes
- LightGBMParams
-
val
numTasks: IntParam
- Definition Classes
- LightGBMExecutionParams
-
val
numThreads: IntParam
- Definition Classes
- LightGBMExecutionParams
-
val
objective: Param[String]
- Definition Classes
- LightGBMObjectiveParams
-
val
objectiveSeed: IntParam
- Definition Classes
- LightGBMSeedParams
-
val
otherRate: DoubleParam
- Definition Classes
- LightGBMLearnerParams
-
val
parallelism: Param[String]
- Definition Classes
- LightGBMExecutionParams
-
lazy val
params: Array[Param[_]]
- Definition Classes
- Params
-
val
passThroughArgs: Param[String]
- Definition Classes
- LightGBMExecutionParams
-
val
posBaggingFraction: DoubleParam
- Definition Classes
- LightGBMFractionParams
-
val
predictDisableShapeCheck: BooleanParam
- Definition Classes
- LightGBMPredictionParams
-
def
prepareDataframe(dataset: Dataset[_], numTasks: Int): DataFrame
- Attributes
- protected
-
def
preprocessData(df: DataFrame): DataFrame
Allow algorithm specific preprocessing of dataset.
Allow algorithm specific preprocessing of dataset.
- df
The dataframe to preprocess prior to training.
- returns
The preprocessed data.
- Attributes
- protected
-
def
pyAdditionalMethods: String
- Definition Classes
- PythonWrappable
-
lazy val
pyClassDoc: String
- Attributes
- protected
- Definition Classes
- PythonWrappable
-
lazy val
pyClassName: String
- Attributes
- protected
- Definition Classes
- PythonWrappable
-
def
pyExtraEstimatorImports: String
- Attributes
- protected
- Definition Classes
- PythonWrappable
-
def
pyExtraEstimatorMethods: String
- Attributes
- protected
- Definition Classes
- PythonWrappable
-
lazy val
pyInheritedClasses: Seq[String]
- Attributes
- protected
- Definition Classes
- PythonWrappable
-
def
pyInitFunc(): String
- Definition Classes
- PythonWrappable
-
lazy val
pyInternalWrapper: Boolean
- Attributes
- protected
- Definition Classes
- PythonWrappable
-
lazy val
pyObjectBaseClass: String
- Attributes
- protected
- Definition Classes
- PythonWrappable
-
def
pyParamArg[T](p: Param[T]): String
- Attributes
- protected
- Definition Classes
- PythonWrappable
-
def
pyParamDefault[T](p: Param[T]): Option[String]
- Attributes
- protected
- Definition Classes
- PythonWrappable
-
def
pyParamGetter(p: Param[_]): String
- Attributes
- protected
- Definition Classes
- PythonWrappable
-
def
pyParamSetter(p: Param[_]): String
- Attributes
- protected
- Definition Classes
- PythonWrappable
-
def
pyParamsArgs: String
- Attributes
- protected
- Definition Classes
- PythonWrappable
-
def
pyParamsDefaults: String
- Attributes
- protected
- Definition Classes
- PythonWrappable
-
lazy val
pyParamsDefinitions: String
- Attributes
- protected
- Definition Classes
- PythonWrappable
-
def
pyParamsGetters: String
- Attributes
- protected
- Definition Classes
- PythonWrappable
-
def
pyParamsSetters: String
- Attributes
- protected
- Definition Classes
- PythonWrappable
-
def
pythonClass(): String
- Attributes
- protected
- Definition Classes
- PythonWrappable
-
def
rClass(): String
- Attributes
- protected
- Definition Classes
- RWrappable
-
def
rDocString: String
- Attributes
- protected
- Definition Classes
- RWrappable
-
def
rExtraBodyLines: String
- Attributes
- protected
- Definition Classes
- RWrappable
-
def
rExtraInitLines: String
- Attributes
- protected
- Definition Classes
- RWrappable
-
lazy val
rFuncName: String
- Attributes
- protected
- Definition Classes
- RWrappable
-
lazy val
rInternalWrapper: Boolean
- Attributes
- protected
- Definition Classes
- RWrappable
-
def
rParamArg[T](p: Param[T]): String
- Attributes
- protected
- Definition Classes
- RWrappable
-
def
rParamsArgs: String
- Attributes
- protected
- Definition Classes
- RWrappable
-
def
rSetterLines: String
- Attributes
- protected
- Definition Classes
- RWrappable
-
val
repartitionByGroupingColumn: BooleanParam
- Definition Classes
- LightGBMExecutionParams
-
def
save(path: String): Unit
- Definition Classes
- MLWritable
- Annotations
- @Since( "1.6.0" ) @throws( ... )
-
val
seed: IntParam
- Definition Classes
- LightGBMSeedParams
-
final
def
set(paramPair: ParamPair[_]): LightGBMBase.this.type
- Attributes
- protected
- Definition Classes
- Params
-
final
def
set(param: String, value: Any): LightGBMBase.this.type
- Attributes
- protected
- Definition Classes
- Params
-
final
def
set[T](param: Param[T], value: T): LightGBMBase.this.type
- Definition Classes
- Params
-
def
setBaggingFraction(value: Double): LightGBMBase.this.type
- Definition Classes
- LightGBMFractionParams
-
def
setBaggingFreq(value: Int): LightGBMBase.this.type
- Definition Classes
- LightGBMParams
-
def
setBaggingSeed(value: Int): LightGBMBase.this.type
- Definition Classes
- LightGBMSeedParams
-
def
setBatchPerformanceMeasure(index: Int, measures: InstrumentationMeasures): Unit
- Attributes
- protected
- Definition Classes
- LightGBMPerformance
-
def
setBatchPerformanceMeasures(measures: Array[Option[InstrumentationMeasures]]): LightGBMBase.this.type
- Attributes
- protected
- Definition Classes
- LightGBMPerformance
-
def
setBinSampleCount(value: Int): LightGBMBase.this.type
- Definition Classes
- LightGBMBinParams
-
def
setBoostFromAverage(value: Boolean): LightGBMBase.this.type
- Definition Classes
- LightGBMParams
-
def
setBoostingType(value: String): LightGBMBase.this.type
- Definition Classes
- LightGBMParams
-
def
setCatSmooth(value: Double): LightGBMBase.this.type
- Definition Classes
- LightGBMCategoricalParams
-
def
setCategoricalSlotIndexes(value: Array[Int]): LightGBMBase.this.type
- Definition Classes
- LightGBMSlotParams
-
def
setCategoricalSlotNames(value: Array[String]): LightGBMBase.this.type
- Definition Classes
- LightGBMSlotParams
-
def
setCatl2(value: Double): LightGBMBase.this.type
- Definition Classes
- LightGBMCategoricalParams
-
def
setChunkSize(value: Int): LightGBMBase.this.type
- Definition Classes
- LightGBMExecutionParams
-
def
setDataRandomSeed(value: Int): LightGBMBase.this.type
- Definition Classes
- LightGBMSeedParams
-
final
def
setDefault(paramPairs: ParamPair[_]*): LightGBMBase.this.type
- Attributes
- protected
- Definition Classes
- Params
-
final
def
setDefault[T](param: Param[T], value: T): LightGBMBase.this.type
- Attributes
- protected
- Definition Classes
- Params
-
def
setDefaultListenPort(value: Int): LightGBMBase.this.type
- Definition Classes
- LightGBMExecutionParams
-
def
setDelegate(delegate: LightGBMDelegate): LightGBMBase.this.type
- Definition Classes
- LightGBMParams
-
def
setDeterministic(value: Boolean): LightGBMBase.this.type
- Definition Classes
- LightGBMSeedParams
-
def
setDriverListenPort(value: Int): LightGBMBase.this.type
- Definition Classes
- LightGBMExecutionParams
-
def
setDropRate(value: Double): LightGBMBase.this.type
- Definition Classes
- LightGBMDartParams
-
def
setDropSeed(value: Int): LightGBMBase.this.type
- Definition Classes
- LightGBMSeedParams
-
def
setEarlyStoppingRound(value: Int): LightGBMBase.this.type
- Definition Classes
- LightGBMLearnerParams
-
def
setExecutionMode(value: String): LightGBMBase.this.type
- Definition Classes
- LightGBMExecutionParams
-
def
setExtraSeed(value: Int): LightGBMBase.this.type
- Definition Classes
- LightGBMSeedParams
-
def
setFObj(value: FObjTrait): LightGBMBase.this.type
- Definition Classes
- LightGBMObjectiveParams
-
def
setFeatureFraction(value: Double): LightGBMBase.this.type
- Definition Classes
- LightGBMFractionParams
-
def
setFeatureFractionByNode(value: Double): LightGBMBase.this.type
- Definition Classes
- LightGBMFractionParams
-
def
setFeatureFractionSeed(value: Int): LightGBMBase.this.type
- Definition Classes
- LightGBMSeedParams
-
def
setFeaturesShapCol(value: String): LightGBMBase.this.type
- Definition Classes
- LightGBMPredictionParams
-
def
setImprovementTolerance(value: Double): LightGBMBase.this.type
- Definition Classes
- LightGBMLearnerParams
-
def
setInitScoreCol(value: String): LightGBMBase.this.type
- Definition Classes
- HasInitScoreCol
-
def
setIsEnableSparse(value: Boolean): LightGBMBase.this.type
- Definition Classes
- LightGBMDatasetParams
-
def
setIsProvideTrainingMetric(value: Boolean): LightGBMBase.this.type
- Definition Classes
- LightGBMParams
-
def
setLambdaL1(value: Double): LightGBMBase.this.type
- Definition Classes
- LightGBMParams
-
def
setLambdaL2(value: Double): LightGBMBase.this.type
- Definition Classes
- LightGBMParams
-
def
setLeafPredictionCol(value: String): LightGBMBase.this.type
- Definition Classes
- LightGBMPredictionParams
-
def
setLearningRate(value: Double): LightGBMBase.this.type
- Definition Classes
- LightGBMParams
-
def
setMatrixType(value: String): LightGBMBase.this.type
- Definition Classes
- LightGBMExecutionParams
-
def
setMaxBin(value: Int): LightGBMBase.this.type
- Definition Classes
- LightGBMBinParams
-
def
setMaxBinByFeature(value: Array[Int]): LightGBMBase.this.type
- Definition Classes
- LightGBMParams
-
def
setMaxCatThreshold(value: Int): LightGBMBase.this.type
- Definition Classes
- LightGBMCategoricalParams
-
def
setMaxCatToOnehot(value: Int): LightGBMBase.this.type
- Definition Classes
- LightGBMCategoricalParams
-
def
setMaxDeltaStep(value: Double): LightGBMBase.this.type
- Definition Classes
- LightGBMParams
-
def
setMaxDepth(value: Int): LightGBMBase.this.type
- Definition Classes
- LightGBMParams
-
def
setMaxDrop(value: Int): LightGBMBase.this.type
- Definition Classes
- LightGBMDartParams
-
def
setMaxNumClasses(value: Int): LightGBMBase.this.type
- Definition Classes
- LightGBMParams
-
def
setMaxStreamingOMPThreads(value: Int): LightGBMBase.this.type
- Definition Classes
- LightGBMExecutionParams
-
def
setMetric(value: String): LightGBMBase.this.type
- Definition Classes
- LightGBMParams
-
def
setMicroBatchSize(value: Int): LightGBMBase.this.type
- Definition Classes
- LightGBMExecutionParams
-
def
setMinDataInLeaf(value: Int): LightGBMBase.this.type
- Definition Classes
- LightGBMParams
-
def
setMinDataPerBin(value: Int): LightGBMBase.this.type
- Definition Classes
- LightGBMParams
-
def
setMinDataPerGroup(value: Int): LightGBMBase.this.type
- Definition Classes
- LightGBMCategoricalParams
-
def
setMinGainToSplit(value: Double): LightGBMBase.this.type
- Definition Classes
- LightGBMParams
-
def
setMinSumHessianInLeaf(value: Double): LightGBMBase.this.type
- Definition Classes
- LightGBMParams
-
def
setModelString(value: String): LightGBMBase.this.type
- Definition Classes
- LightGBMParams
-
def
setMonotoneConstraints(value: Array[Int]): LightGBMBase.this.type
- Definition Classes
- LightGBMLearnerParams
-
def
setMonotoneConstraintsMethod(value: String): LightGBMBase.this.type
- Definition Classes
- LightGBMLearnerParams
-
def
setMonotonePenalty(value: Double): LightGBMBase.this.type
- Definition Classes
- LightGBMLearnerParams
-
def
setNegBaggingFraction(value: Double): LightGBMBase.this.type
- Definition Classes
- LightGBMFractionParams
-
def
setNumBatches(value: Int): LightGBMBase.this.type
- Definition Classes
- LightGBMExecutionParams
-
def
setNumIterations(value: Int): LightGBMBase.this.type
- Definition Classes
- LightGBMParams
-
def
setNumLeaves(value: Int): LightGBMBase.this.type
- Definition Classes
- LightGBMParams
-
def
setNumTasks(value: Int): LightGBMBase.this.type
- Definition Classes
- LightGBMExecutionParams
-
def
setNumThreads(value: Int): LightGBMBase.this.type
- Definition Classes
- LightGBMExecutionParams
-
def
setObjective(value: String): LightGBMBase.this.type
- Definition Classes
- LightGBMObjectiveParams
-
def
setObjectiveSeed(value: Int): LightGBMBase.this.type
- Definition Classes
- LightGBMSeedParams
-
def
setOtherRate(value: Double): LightGBMBase.this.type
- Definition Classes
- LightGBMLearnerParams
-
def
setParallelism(value: String): LightGBMBase.this.type
- Definition Classes
- LightGBMExecutionParams
-
def
setPassThroughArgs(value: String): LightGBMBase.this.type
- Definition Classes
- LightGBMExecutionParams
-
def
setPosBaggingFraction(value: Double): LightGBMBase.this.type
- Definition Classes
- LightGBMFractionParams
-
def
setPredictDisableShapeCheck(value: Boolean): LightGBMBase.this.type
- Definition Classes
- LightGBMPredictionParams
-
def
setRepartitionByGroupingColumn(value: Boolean): LightGBMBase.this.type
- Definition Classes
- LightGBMExecutionParams
-
def
setSeed(value: Int): LightGBMBase.this.type
- Definition Classes
- LightGBMSeedParams
-
def
setSkipDrop(value: Double): LightGBMBase.this.type
- Definition Classes
- LightGBMDartParams
-
def
setSlotNames(value: Array[String]): LightGBMBase.this.type
- Definition Classes
- LightGBMSlotParams
-
def
setTimeout(value: Double): LightGBMBase.this.type
- Definition Classes
- LightGBMExecutionParams
-
def
setTopK(value: Int): LightGBMBase.this.type
- Definition Classes
- LightGBMExecutionParams
-
def
setTopRate(value: Double): LightGBMBase.this.type
- Definition Classes
- LightGBMLearnerParams
-
def
setUniformDrop(value: Boolean): LightGBMBase.this.type
- Definition Classes
- LightGBMDartParams
-
def
setUseBarrierExecutionMode(value: Boolean): LightGBMBase.this.type
- Definition Classes
- LightGBMExecutionParams
-
def
setUseMissing(value: Boolean): LightGBMBase.this.type
- Definition Classes
- LightGBMDatasetParams
-
def
setUseSingleDatasetMode(value: Boolean): LightGBMBase.this.type
- Definition Classes
- LightGBMExecutionParams
-
def
setValidationIndicatorCol(value: String): LightGBMBase.this.type
- Definition Classes
- HasValidationIndicatorCol
-
def
setVerbosity(value: Int): LightGBMBase.this.type
- Definition Classes
- LightGBMParams
-
def
setWeightCol(value: String): LightGBMBase.this.type
- Definition Classes
- HasWeightCol
-
def
setXGBoostDartMode(value: Boolean): LightGBMBase.this.type
- Definition Classes
- LightGBMDartParams
-
def
setZeroAsMissing(value: Boolean): LightGBMBase.this.type
- Definition Classes
- LightGBMDatasetParams
-
val
skipDrop: DoubleParam
- Definition Classes
- LightGBMDartParams
-
val
slotNames: StringArrayParam
- Definition Classes
- LightGBMSlotParams
-
final
def
synchronized[T0](arg0: ⇒ T0): T0
- Definition Classes
- AnyRef
-
val
thisStage: Params
- Attributes
- protected
- Definition Classes
- BaseWrappable
-
val
timeout: DoubleParam
- Definition Classes
- LightGBMExecutionParams
-
def
toString(): String
- Definition Classes
- Identifiable → AnyRef → Any
-
val
topK: IntParam
- Definition Classes
- LightGBMExecutionParams
-
val
topRate: DoubleParam
- Definition Classes
- LightGBMLearnerParams
-
def
train(dataset: Dataset[_]): TrainedModel
Trains the LightGBM model.
Trains the LightGBM model. If batches are specified, breaks training dataset into batches for training.
- dataset
The input dataset to train.
- returns
The trained model.
- Attributes
- protected
-
def
trainOneDataBatch(dataset: Dataset[_], batchIndex: Int, batchCount: Int): TrainedModel
Inner train method for LightGBM learners.
Inner train method for LightGBM learners. Calculates the number of workers, creates a driver thread, and runs mapPartitions on the dataset.
- dataset
The dataset to train on.
- batchIndex
In running in batch training mode, gets the batch number.
- returns
The LightGBM Model from the trained LightGBM Booster.
- Attributes
- protected
-
def
transformSchema(schema: StructType, logging: Boolean): StructType
- Attributes
- protected
- Definition Classes
- PipelineStage
- Annotations
- @DeveloperApi()
-
val
uniformDrop: BooleanParam
- Definition Classes
- LightGBMDartParams
-
val
useBarrierExecutionMode: BooleanParam
- Definition Classes
- LightGBMExecutionParams
-
val
useMissing: BooleanParam
- Definition Classes
- LightGBMDatasetParams
-
val
useSingleDatasetMode: BooleanParam
- Definition Classes
- LightGBMExecutionParams
-
val
validationIndicatorCol: Param[String]
The name of the validation indicator column
The name of the validation indicator column
- Definition Classes
- HasValidationIndicatorCol
-
val
verbosity: IntParam
- Definition Classes
- LightGBMParams
-
final
def
wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... )
-
final
def
wait(arg0: Long, arg1: Int): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... )
-
final
def
wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... ) @native()
-
val
weightCol: Param[String]
The name of the weight column
The name of the weight column
- Definition Classes
- HasWeightCol
-
def
write: MLWriter
- Definition Classes
- DefaultParamsWritable → MLWritable
-
val
xGBoostDartMode: BooleanParam
- Definition Classes
- LightGBMDartParams
-
val
zeroAsMissing: BooleanParam
- Definition Classes
- LightGBMDatasetParams