Instance Constructors
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new
H2OGBMMOJOModel(uid: String)
Value Members
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final
def
!=(arg0: Any): Boolean
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final
def
##(): Int
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final
def
$[T](param: Param[T]): T
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final
def
==(arg0: Any): Boolean
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def
applyPredictionUdf(dataset: Dataset[_], udfConstructor: (Array[String]) ⇒ UserDefinedFunction): DataFrame
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def
applyPredictionUdfToFlatDataFrame(flatDataFrame: DataFrame, udfConstructor: (Array[String]) ⇒ UserDefinedFunction, inputs: Array[String]): DataFrame
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final
def
asInstanceOf[T0]: T0
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val
balanceClasses: BooleanParam
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def
booleanParam(name: String, doc: String): BooleanParam
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val
buildTreeOneNode: BooleanParam
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val
calibrateModel: BooleanParam
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val
checkConstantResponse: BooleanParam
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final
def
clear(param: Param[_]): H2OGBMMOJOModel.this.type
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def
clone(): AnyRef
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val
colSampleRate: DoubleParam
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val
colSampleRateChangePerLevel: DoubleParam
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val
colSampleRatePerTree: DoubleParam
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final
val
convertInvalidNumbersToNa: BooleanParam
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final
val
convertUnknownCategoricalLevelsToNa: BooleanParam
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def
copy(extra: ParamMap): H2OMOJOModel
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def
copyValues[T <: Params](to: T, extra: ParamMap): T
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var
crossValidationModels: Array[H2OMOJOModel]
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final
val
dataFrameSerializer: Param[String]
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final
def
defaultCopy[T <: Params](extra: ParamMap): T
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final
val
defaultThreshold: DoubleParam
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final
val
detailedPredictionCol: Param[String]
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def
doubleArrayParam(name: String, doc: String): DoubleArrayParam
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def
doubleParam(name: String, doc: String): DoubleParam
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final
val
endTime: LongParam
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final
def
eq(arg0: AnyRef): Boolean
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def
equals(arg0: Any): Boolean
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def
explainParam(param: Param[_]): String
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def
explainParams(): String
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def
extractAnomalyPredictionColContent(): Column
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def
extractBinomialPredictionColContent(): Column
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def
extractClusteringPredictionColContent(): Column
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def
extractCoxPHPredictionColContent(): Column
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def
extractCrossValidationMetricsSummary(modelJson: JsonObject): DataFrame
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def
extractDimReductionSimplePredictionColContent(): Column
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def
extractFeatureImportances(outputJson: JsonObject): DataFrame
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def
extractFeatureTypes(outputJson: JsonObject): Map[String, String]
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def
extractJsonFieldValue[T](outputJson: JsonObject, fieldName: String, getValue: (JsonElement) ⇒ T, defaultValue: T): T
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def
extractMetrics(json: JsonObject, metricType: String): Map[String, Double]
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def
extractMetricsObject(json: JsonObject, metricType: String, algoName: String, modelCategory: internals.H2OModelCategory.Value, dataFrameSerializerGetter: () ⇒ String): H2OMetrics
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def
extractModelCategory(outputJson: JsonObject): internals.H2OModelCategory.Value
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def
extractMultinomialPredictionColContent(): Column
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def
extractOrdinalPredictionColContent(): Column
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final
def
extractParamMap(): ParamMap
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final
def
extractParamMap(extra: ParamMap): ParamMap
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def
extractParams(modelJson: JsonObject): Map[String, String]
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def
extractPredictionColContent(): Column
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def
extractRegressionPredictionColContent(): Column
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def
extractScoringHistory(outputJson: JsonObject): DataFrame
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def
extractWordEmbeddingPredictionColContent(): Column
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final
val
featuresCols: StringArrayParam
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def
finalize(): Unit
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def
floatParam(name: String, doc: String): FloatParam
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val
gainsliftBins: IntParam
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final
def
get[T](param: Param[T]): Option[T]
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def
getAnomalyPredictionColSchema(): Seq[StructField]
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def
getAnomalyPredictionSchema(): StructType
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def
getAnomalyPredictionUDF(): UserDefinedFunction
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def
getAucType(): String
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def
getBalanceClasses(): Boolean
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def
getBinomialPredictionColSchema(): Seq[StructField]
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def
getBinomialPredictionSchema(): StructType
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def
getBinomialPredictionUDF(): UserDefinedFunction
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def
getBuildTreeOneNode(): Boolean
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def
getCalibrateModel(): Boolean
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def
getCategoricalEncoding(): String
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def
getCheckConstantResponse(): Boolean
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final
def
getClass(): Class[_]
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def
getClassSamplingFactors(): Array[Float]
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def
getClusteringPredictionColSchema(): Seq[StructField]
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def
getClusteringPredictionSchema(): StructType
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def
getClusteringPredictionUDF(): UserDefinedFunction
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def
getColSampleRate(): Double
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def
getColSampleRateChangePerLevel(): Double
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def
getColSampleRatePerTree(): Double
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def
getContributionsSchema(model: EasyPredictModelWrapper): DataType
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def
getConvertInvalidNumbersToNa(): Boolean
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def
getConvertUnknownCategoricalLevelsToNa(): Boolean
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def
getCoxPHPredictionColSchema(): Seq[StructField]
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def
getCoxPHPredictionSchema(): StructType
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def
getCoxPHPredictionUDF(): UserDefinedFunction
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def
getCrossValidationMetrics(): Map[String, Double]
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def
getCrossValidationMetricsObject(): H2OMetrics
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def
getCrossValidationMetricsSummary(): DataFrame
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def
getCrossValidationModels(): Seq[H2OGBMMOJOModel.this.type]
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def
getCurrentMetrics(): Map[String, Double]
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def
getCurrentMetricsObject(): H2OMetrics
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def
getCustomDistributionFunc(): String
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def
getCustomMetricFunc(): String
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def
getDataFrameSerializer(): String
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final
def
getDefault[T](param: Param[T]): Option[T]
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def
getDefaultThreshold(): Double
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def
getDetailedPredictionCol(): String
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def
getDetailedPredictionColSchema(): Seq[StructField]
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def
getDimReductionPredictionColSchema(): Seq[StructField]
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def
getDimReductionPredictionSchema(): StructType
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def
getDimReductionPredictionUDF(): UserDefinedFunction
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def
getDistribution(): String
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def
getDomainValues(): Map[String, Array[String]]
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def
getEndTime(): Long
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def
getExportCheckpointsDir(): String
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def
getFeatureImportances(): DataFrame
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def
getFeatureTypes(): Map[String, String]
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def
getFeaturesCols(): Array[String]
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def
getFoldAssignment(): String
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def
getFoldCol(): String
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def
getGainsliftBins(): Int
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def
getHistogramType(): String
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def
getHuberAlpha(): Double
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def
getIgnoreConstCols(): Boolean
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def
getIgnoredCols(): Array[String]
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def
getKeepCrossValidationFoldAssignment(): Boolean
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def
getKeepCrossValidationModels(): Boolean
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def
getKeepCrossValidationPredictions(): Boolean
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def
getLabelCol(): String
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def
getLearnRate(): Double
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def
getLearnRateAnnealing(): Double
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def
getMaxAbsLeafnodePred(): Double
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def
getMaxAfterBalanceSize(): Float
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def
getMaxConfusionMatrixSize(): Int
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def
getMaxDepth(): Int
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def
getMaxRuntimeSecs(): Double
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def
getMinRows(): Double
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def
getMinSplitImprovement(): Double
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def
getModelCategory(): String
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def
getModelDetails(): String
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def
getModelDetails(modelJson: JsonObject): String
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def
getModelJson(mojo: File): JsonObject
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def
getMonotoneConstraints(): Map[String, Double]
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def
getMultinomialPredictionColSchema(): Seq[StructField]
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def
getMultinomialPredictionSchema(): StructType
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def
getMultinomialPredictionUDF(): UserDefinedFunction
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def
getNamedMojoOutputColumns(): Boolean
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def
getNbins(): Int
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def
getNbinsCats(): Int
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def
getNbinsTopLevel(): Int
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def
getNfolds(): Int
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def
getNtrees(): Int
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def
getOffsetCol(): String
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final
def
getOrDefault[T](param: Param[T]): T
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def
getOrdinalPredictionColSchema(): Seq[StructField]
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def
getOrdinalPredictionSchema(): StructType
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def
getOrdinalPredictionUDF(): UserDefinedFunction
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def
getParam(paramName: String): Param[Any]
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def
getPredNoiseBandwidth(): Double
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def
getPredictionCol(): String
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def
getPredictionColSchema(): Seq[StructField]
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def
getPredictionSchema(): StructType
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def
getPredictionUDF(): UserDefinedFunction
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def
getQuantileAlpha(): Double
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def
getRegressionPredictionColSchema(): Seq[StructField]
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def
getRegressionPredictionSchema(): StructType
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def
getRegressionPredictionUDF(): UserDefinedFunction
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def
getRelevantColumnNames(flatDataFrame: DataFrame, inputs: Array[String]): Array[String]
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def
getRunTime(): Long
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def
getSampleRate(): Double
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def
getSampleRatePerClass(): Array[Double]
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def
getScoreEachIteration(): Boolean
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def
getScoreTreeInterval(): Int
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def
getScoringHistory(): DataFrame
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def
getSeed(): Long
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def
getStageProbabilitiesSchema(model: EasyPredictModelWrapper): DataType
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def
getStartTime(): Long
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def
getStoppingMetric(): String
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def
getStoppingRounds(): Int
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def
getStoppingTolerance(): Double
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def
getTrainingMetrics(): Map[String, Double]
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def
getTrainingMetricsObject(): H2OMetrics
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def
getTrainingParams(): Map[String, String]
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def
getTweediePower(): Double
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def
getValidationMetrics(): Map[String, Double]
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def
getValidationMetricsObject(): H2OMetrics
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def
getWeightCol(): String
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def
getWithContributions(): Boolean
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def
getWithLeafNodeAssignments(): Boolean
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def
getWithStageResults(): Boolean
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def
getWordEmbeddingPredictionColSchema(): Seq[StructField]
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def
getWordEmbeddingPredictionSchema(): StructType
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def
getWordEmbeddingPredictionUDF(): UserDefinedFunction
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final
def
hasDefault[T](param: Param[T]): Boolean
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def
hasParam(paramName: String): Boolean
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def
hasParent: Boolean
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def
hashCode(): Int
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val
huberAlpha: DoubleParam
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val
ignoreConstCols: BooleanParam
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def
initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
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def
initializeLogIfNecessary(isInterpreter: Boolean): Unit
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def
inputColumnNames: Array[String]
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def
intArrayParam(name: String, doc: String): IntArrayParam
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def
intParam(name: String, doc: String): IntParam
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final
def
isDefined(param: Param[_]): Boolean
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final
def
isInstanceOf[T0]: Boolean
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final
def
isSet(param: Param[_]): Boolean
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def
isTraceEnabled(): Boolean
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def
jsonFieldToDataFrame(outputJson: JsonObject, fieldName: String): DataFrame
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def
jsonFieldToDoubleArray(outputJson: JsonObject, fieldName: String): Array[Double]
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val
keepCrossValidationFoldAssignment: BooleanParam
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val
keepCrossValidationModels: BooleanParam
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val
keepCrossValidationPredictions: BooleanParam
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val
labelCol: Param[String]
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val
learnRate: DoubleParam
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val
learnRateAnnealing: DoubleParam
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def
log: Logger
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def
logDebug(msg: ⇒ String, throwable: Throwable): Unit
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def
logDebug(msg: ⇒ String): Unit
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def
logError(msg: ⇒ String, throwable: Throwable): Unit
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def
logError(msg: ⇒ String): Unit
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def
logInfo(msg: ⇒ String, throwable: Throwable): Unit
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def
logInfo(msg: ⇒ String): Unit
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def
logName: String
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def
logTrace(msg: ⇒ String, throwable: Throwable): Unit
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def
logTrace(msg: ⇒ String): Unit
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def
logWarning(msg: ⇒ String, throwable: Throwable): Unit
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def
logWarning(msg: ⇒ String): Unit
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def
longParam(name: String, doc: String): LongParam
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val
maxAbsLeafnodePred: DoubleParam
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val
maxAfterBalanceSize: FloatParam
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val
maxConfusionMatrixSize: IntParam
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val
maxDepth: IntParam
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val
maxRuntimeSecs: DoubleParam
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val
minRows: DoubleParam
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val
minSplitImprovement: DoubleParam
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final
val
namedMojoOutputColumns: Param[Boolean]
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val
nbins: IntParam
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val
nbinsCats: IntParam
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val
nbinsTopLevel: IntParam
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final
def
ne(arg0: AnyRef): Boolean
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val
nfolds: IntParam
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final
def
notify(): Unit
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final
def
notifyAll(): Unit
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final
val
ntrees: IntParam
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def
nullableDataFrameParam(name: String, doc: String): NullableDataFrameParam
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def
nullableDoubleArrayArrayParam(name: String, doc: String): NullableDoubleArrayArrayParam
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def
nullableDoubleArrayParam(name: String, doc: String): NullableDoubleArrayParam
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def
nullableFloatArrayParam(name: String, doc: String): NullableFloatArrayParam
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def
nullableIntArrayParam(name: String, doc: String): NullableIntArrayParam
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def
nullableStringArrayArrayParam(name: String, doc: String): NullableStringArrayArrayParam
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def
nullableStringArrayParam(name: String, doc: String): NullableStringArrayParam
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def
nullableStringPairArrayParam(name: String, doc: String): NullableStringPairArrayParam
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def
nullableStringParam(name: String, doc: String): NullableStringParam
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def
outputColumnName: String
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def
param[T](name: String, doc: String): Param[T]
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lazy val
params: Array[Param[_]]
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val
predNoiseBandwidth: DoubleParam
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final
val
predictionCol: Param[String]
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val
quantileAlpha: DoubleParam
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final
val
runTime: LongParam
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val
sampleRate: DoubleParam
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def
save(path: String): Unit
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val
scoreEachIteration: BooleanParam
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val
scoreTreeInterval: IntParam
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val
seed: LongParam
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final
def
set(paramPair: ParamPair[_]): H2OGBMMOJOModel.this.type
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final
def
set(param: String, value: Any): H2OGBMMOJOModel.this.type
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final
def
set[T](param: Param[T], value: T): H2OGBMMOJOModel.this.type
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def
setDataFrameSerializer(fullClassName: String): H2OGBMMOJOModel.this.type
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final
def
setDefault(paramPairs: ParamPair[_]*): H2OGBMMOJOModel.this.type
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final
def
setDefault[T](param: Param[T], value: T): H2OGBMMOJOModel.this.type
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def
setMojo(mojo: File): H2OGBMMOJOModel.this.type
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def
setMojo(mojo: InputStream, mojoName: String): H2OGBMMOJOModel.this.type
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def
setMojo(mojo: InputStream): H2OGBMMOJOModel.this.type
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final
val
startTime: LongParam
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val
stoppingRounds: IntParam
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val
stoppingTolerance: DoubleParam
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def
stringArrayParam(name: String, doc: String): StringArrayParam
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def
stringParam(name: String, doc: String): Param[String]
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final
def
synchronized[T0](arg0: ⇒ T0): T0
-
def
toString(): String
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-
-
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def
transform(dataset: Dataset[_]): DataFrame
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def
transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
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def
transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
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def
transformSchema(schema: StructType): StructType
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def
transformSchema(schema: StructType, logging: Boolean): StructType
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val
tweediePower: DoubleParam
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val
uid: String
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def
unwrapMojoModel(): MojoModel
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-
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final
def
wait(): Unit
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final
def
wait(arg0: Long, arg1: Int): Unit
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final
def
wait(arg0: Long): Unit
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final
val
withContributions: BooleanParam
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final
val
withLeafNodeAssignments: BooleanParam
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final
val
withStageResults: BooleanParam
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def
write: MLWriter
Inherited from Logging
Inherited from MLWritable
Inherited from HasMojo
Inherited from Transformer
Inherited from PipelineStage
Inherited from Logging
Inherited from Params
Inherited from Serializable
Inherited from Serializable
Inherited from Identifiable
Inherited from AnyRef
Inherited from Any