H2OSupervisedAlgorithm

abstract def paramTag: ClassTag[P]

abstract def schemaTag: ClassTag[H2O_SCHEMA]

abstract val uid: String

final def !=(arg0: Any): Boolean

final def ##(): Int

final def $[T](param: Param[T]): T

final def ==(arg0: Any): Boolean

final val allStringColumnsToCategorical: BooleanParam

final def asInstanceOf[T0]: T0

def booleanParam(name: String, doc: Option[String] = None): BooleanParam

def booleanParam(name: String, doc: String): BooleanParam

final def clear(param: Param[_]): H2OSupervisedAlgorithm.this.type

def clone(): AnyRef

final val columnsToCategorical: StringArrayParam

final val convertInvalidNumbersToNa: BooleanParam

final val convertUnknownCategoricalLevelsToNa: BooleanParam

def copy(extra: ParamMap): H2OSupervisedAlgorithm.this.type

def copyValues[T <: Params](to: T, extra: ParamMap): T

final def defaultCopy[T <: Params](extra: ParamMap): T

final val detailedPredictionCol: Param[String]

def doubleArrayParam(name: String, doc: Option[String] = None): DoubleArrayParam

def doubleArrayParam(name: String, doc: String): DoubleArrayParam

def doubleParam(name: String, doc: Option[String] = None): DoubleParam

def doubleParam(name: String, doc: String): DoubleParam

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def explainParam(param: Param[_]): String

def explainParams(): String

final def extractParamMap(): ParamMap

final def extractParamMap(extra: ParamMap): ParamMap

final val featuresCols: StringArrayParam

def finalize(): Unit

def fit(dataset: Dataset[_]): H2OMOJOModel

def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[H2OMOJOModel]

def fit(dataset: Dataset[_], paramMap: ParamMap): H2OMOJOModel

def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): H2OMOJOModel

def floatParam(name: String, doc: Option[String] = None): FloatParam

def floatParam(name: String, doc: String): FloatParam

final val foldCol: NullableStringParam

final def get[T](param: Param[T]): Option[T]

def getAllStringColumnsToCategorical(): Boolean

final def getClass(): Class[_]

def getColumnsToCategorical(): Array[String]

def getConvertInvalidNumbersToNa(): Boolean

def getConvertUnknownCategoricalLevelsToNa(): Boolean

final def getDefault[T](param: Param[T]): Option[T]

def getDetailedPredictionCol(): String

def getDistribution(): String

def getDoc(doc: Option[String], fieldName: String): String

def getExcludedCols(): Seq[String]

def getFeaturesCols(): Array[String]

def getFoldCol(): String

def getH2ODoc(fieldName: String): String

def getKeepCrossValidationFoldAssignment(): Boolean

def getKeepCrossValidationPredictions(): Boolean

def getLabelCol(): String

def getModelId(): String

def getNamedMojoOutputColumns(): Boolean

def getNfolds(): Int

final def getOrDefault[T](param: Param[T]): T

def getParallelizeCrossValidation(): Boolean

def getParam(paramName: String): Param[Any]

def getPredictionCol(): String

def getSeed(): Long

def getSplitRatio(): Double

def getWeightCol(): String

def getWithDetailedPredictionCol(): Boolean

final def hasDefault[T](param: Param[T]): Boolean

def hasParam(paramName: String): Boolean

def hashCode(): Int

def initializeLogIfNecessary(isInterpreter: Boolean): Unit

def intArrayParam(name: String, doc: Option[String] = None): IntArrayParam

def intArrayParam(name: String, doc: String): IntArrayParam

def intParam(name: String, doc: Option[String] = None): IntParam

def intParam(name: String, doc: String): IntParam

final def isDefined(param: Param[_]): Boolean

final def isInstanceOf[T0]: Boolean

final def isSet(param: Param[_]): Boolean

def isTraceEnabled(): Boolean

final val labelCol: Param[String]

def log: Logger

def logDebug(msg: ⇒ String, throwable: Throwable): Unit

def logDebug(msg: ⇒ String): Unit

def logError(msg: ⇒ String, throwable: Throwable): Unit

def logError(msg: ⇒ String): Unit

def logInfo(msg: ⇒ String, throwable: Throwable): Unit

def logInfo(msg: ⇒ String): Unit

def logName: String

def logTrace(msg: ⇒ String, throwable: Throwable): Unit

def logTrace(msg: ⇒ String): Unit

def logWarning(msg: ⇒ String, throwable: Throwable): Unit

def logWarning(msg: ⇒ String): Unit

def longParam(name: String, doc: Option[String] = None): LongParam

def longParam(name: String, doc: String): LongParam

final val modelId: NullableStringParam

final val namedMojoOutputColumns: Param[Boolean]

final def ne(arg0: AnyRef): Boolean

final val nfolds: IntParam

final def notify(): Unit

final def notifyAll(): Unit

def nullableDoubleArrayArrayParam(name: String, doc: Option[String] = None): NullableDoubleArrayArrayParam

def nullableDoubleArrayArrayParam(name: String, doc: String): NullableDoubleArrayArrayParam

def nullableDoubleArrayParam(name: String, doc: Option[String] = None): NullableDoubleArrayParam

def nullableDoubleArrayParam(name: String, doc: String): NullableDoubleArrayParam

def nullableStringArrayParam(name: String, doc: Option[String] = None): NullableStringArrayParam

def nullableStringArrayParam(name: String, doc: String): NullableStringArrayParam

def nullableStringParam(name: String, doc: Option[String] = None): NullableStringParam

def nullableStringParam(name: String, doc: String): NullableStringParam

def param[T](name: String, doc: Option[String] = None): Param[T]

def param[T](name: String, doc: String): Param[T]

var parameters: P

lazy val params: Array[Param[_]]

def preProcessBeforeFit(trainFrame: Frame): Unit

final val predictionCol: Param[String]

def prepareDatasetForFitting(dataset: Dataset[_]): (Frame, Option[Frame], Array[String])

def save(path: String): Unit

final val seed: LongParam

final def set(paramPair: ParamPair[_]): H2OSupervisedAlgorithm.this.type

final def set(param: String, value: Any): H2OSupervisedAlgorithm.this.type

final def set[T](param: Param[T], value: T): H2OSupervisedAlgorithm.this.type

def setAllStringColumnsToCategorical(value: Boolean): H2OSupervisedAlgorithm.this.type

def setColumnsToCategorical(columns: Array[String]): H2OSupervisedAlgorithm.this.type

def setColumnsToCategorical(first: String, others: String*): H2OSupervisedAlgorithm.this.type

def setConvertInvalidNumbersToNa(value: Boolean): H2OSupervisedAlgorithm.this.type

def setConvertUnknownCategoricalLevelsToNa(value: Boolean): H2OSupervisedAlgorithm.this.type

final def setDefault(paramPairs: ParamPair[_]*): H2OSupervisedAlgorithm.this.type

final def setDefault[T](param: Param[T], value: T): H2OSupervisedAlgorithm.this.type

def setDetailedPredictionCol(columnName: String): H2OSupervisedAlgorithm.this.type

def setDistribution(value: String): H2OSupervisedAlgorithm.this.type

def setDistribution(value: DistributionFamily): H2OSupervisedAlgorithm.this.type

def setFeaturesCol(first: String): H2OSupervisedAlgorithm.this.type

def setFeaturesCols(columnNames: Array[String]): H2OSupervisedAlgorithm.this.type

def setFeaturesCols(first: String, others: String*): H2OSupervisedAlgorithm.this.type

def setFoldCol(columnName: String): H2OSupervisedAlgorithm.this.type

def setKeepCrossValidationFoldAssignment(value: Boolean): H2OSupervisedAlgorithm.this.type

def setKeepCrossValidationPredictions(value: Boolean): H2OSupervisedAlgorithm.this.type

def setLabelCol(columnName: String): H2OSupervisedAlgorithm.this.type

def setModelId(id: String): H2OSupervisedAlgorithm.this.type

def setNamedMojoOutputColumns(value: Boolean): H2OSupervisedAlgorithm.this.type

def setNfolds(value: Int): H2OSupervisedAlgorithm.this.type

def setParallelizeCrossValidation(value: Boolean): H2OSupervisedAlgorithm.this.type

def setPredictionCol(columnName: String): H2OSupervisedAlgorithm.this.type

def setSeed(value: Long): H2OSupervisedAlgorithm.this.type

def setSplitRatio(ratio: Double): H2OSupervisedAlgorithm.this.type

def setWeightCol(columnName: String): H2OSupervisedAlgorithm.this.type

def setWithDetailedPredictionCol(enabled: Boolean): H2OSupervisedAlgorithm.this.type

final val splitRatio: DoubleParam

def stringArrayParam(name: String, doc: Option[String] = None): StringArrayParam

def stringArrayParam(name: String, doc: String): StringArrayParam

def stringParam(name: String, doc: Option[String] = None): Param[String]

def stringParam(name: String, doc: String): Param[String]

final def synchronized[T0](arg0: ⇒ T0): T0

def toString(): String

def transformSchema(schema: StructType): StructType

def transformSchema(schema: StructType, logging: Boolean): StructType

def updateH2OParams(): Unit

Update H2O params based on provided parameters to Spark Transformer/Estimator

final def wait(): Unit

final def wait(arg0: Long, arg1: Int): Unit

final def wait(arg0: Long): Unit

final val weightCol: NullableStringParam

final val withDetailedPredictionCol: BooleanParam

def write: MLWriter