Instance Constructors
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new
H2OGAMMOJOModel(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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val
betaEpsilon: DoubleParam
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def
booleanParam(name: String, doc: String): BooleanParam
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final
def
clear(param: Param[_]): H2OGAMMOJOModel.this.type
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def
clone(): AnyRef
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val
coldStart: BooleanParam
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val
computePValues: BooleanParam
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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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final
def
defaultCopy[T <: Params](extra: ParamMap): T
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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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val
earlyStopping: BooleanParam
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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
extractAutoEncoderPredictionColContent(): Column
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def
extractBinomialPredictionColContent(): Column
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def
extractClusteringPredictionColContent(): Column
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def
extractDimReductionSimplePredictionColContent(): Column
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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
extractPredictionColContent(): Column
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def
extractRegressionPredictionColContent(): Column
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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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final
def
get[T](param: Param[T]): Option[T]
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def
getAlphaValue(): Array[Double]
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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
getAutoEncoderPredictionColSchema(): Seq[StructField]
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def
getAutoEncoderPredictionSchema(): StructType
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def
getAutoEncoderPredictionUDF(): UserDefinedFunction
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def
getBalanceClasses(): Boolean
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def
getBetaEpsilon(): Double
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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
getBs(): Array[Int]
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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
getColdStart(): Boolean
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def
getComputePValues(): Boolean
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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
getCrossValidationMetrics(): Map[String, Double]
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def
getCurrentMetrics(): Map[String, Double]
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def
getCustomMetricFunc(): String
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final
def
getDefault[T](param: Param[T]): Option[T]
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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
getDomainValues(): Map[String, Array[String]]
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def
getEarlyStopping(): Boolean
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def
getExportCheckpointsDir(): String
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def
getFamily(): String
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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
getGamCols(): Array[String]
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def
getGradientEpsilon(): Double
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def
getIgnoreConstCols(): Boolean
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def
getIgnoredCols(): Array[String]
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def
getInteractions(): Array[String]
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def
getIntercept(): Boolean
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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
getKeepGamCols(): Boolean
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def
getKnotIds(): Array[String]
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def
getLabelCol(): String
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def
getLambdaSearch(): Boolean
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def
getLambdaValue(): Array[Double]
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def
getLink(): String
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def
getMaxActivePredictors(): Int
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def
getMaxAfterBalanceSize(): Float
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def
getMaxConfusionMatrixSize(): Int
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def
getMaxIterations(): Int
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def
getMaxRuntimeSecs(): Double
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def
getMissingValuesHandling(): String
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def
getModelCategory(): String
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def
getModelDetails(): String
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def
getMojo(): File
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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
getNfolds(): Int
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def
getNlambdas(): Int
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def
getNonNegative(): Boolean
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def
getNumKnots(): Array[Int]
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def
getObjReg(): Double
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def
getObjectiveEpsilon(): Double
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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
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
getPrior(): 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
getRemoveCollinearCols(): Boolean
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def
getScale(): Array[Double]
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def
getScoreEachIteration(): Boolean
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def
getSolver(): String
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def
getStageProbabilitiesSchema(model: EasyPredictModelWrapper): DataType
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def
getStandardize(): Boolean
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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
getTheta(): Double
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def
getTrainingMetrics(): Map[String, Double]
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def
getTrainingParams(): Map[String, String]
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def
getTweedieLinkPower(): Double
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def
getTweedieVariancePower(): Double
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def
getValidationMetrics(): Map[String, Double]
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def
getWeightCol(): String
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def
getWithContributions(): Boolean
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def
getWithDetailedPredictionCol(): 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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val
gradientEpsilon: DoubleParam
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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
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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val
intercept: BooleanParam
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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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val
keepCrossValidationFoldAssignment: BooleanParam
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val
keepCrossValidationModels: BooleanParam
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val
keepCrossValidationPredictions: BooleanParam
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val
keepGamCols: BooleanParam
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val
labelCol: Param[String]
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val
lambdaSearch: BooleanParam
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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
maxActivePredictors: IntParam
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val
maxAfterBalanceSize: FloatParam
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val
maxConfusionMatrixSize: IntParam
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val
maxIterations: IntParam
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val
maxRuntimeSecs: DoubleParam
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final
val
namedMojoOutputColumns: Param[Boolean]
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final
def
ne(arg0: AnyRef): Boolean
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val
nfolds: IntParam
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val
nlambdas: IntParam
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val
nonNegative: BooleanParam
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final
def
notify(): Unit
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final
def
notifyAll(): Unit
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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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val
objReg: DoubleParam
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val
objectiveEpsilon: DoubleParam
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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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final
val
predictionCol: Param[String]
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val
prior: DoubleParam
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val
removeCollinearCols: BooleanParam
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def
save(path: String): Unit
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val
scoreEachIteration: BooleanParam
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final
def
set(paramPair: ParamPair[_]): H2OGAMMOJOModel.this.type
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final
def
set(param: String, value: Any): H2OGAMMOJOModel.this.type
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final
def
set[T](param: Param[T], value: T): H2OGAMMOJOModel.this.type
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final
def
setDefault(paramPairs: ParamPair[_]*): H2OGAMMOJOModel.this.type
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final
def
setDefault[T](param: Param[T], value: T): H2OGAMMOJOModel.this.type
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def
setMojo(mojo: File): H2OGAMMOJOModel.this.type
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def
setMojo(mojo: InputStream, mojoName: String): H2OGAMMOJOModel.this.type
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def
setMojo(mojo: InputStream): H2OGAMMOJOModel.this.type
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val
standardize: BooleanParam
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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
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val
theta: DoubleParam
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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
tweedieLinkPower: DoubleParam
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val
tweedieVariancePower: DoubleParam
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val
uid: String
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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
-
final
val
withDetailedPredictionCol: 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 MLWritable
Inherited from HasMojo
Inherited from Logging
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