H2ODeepLearning

final def !=(arg0: Any): Boolean

final def ##(): Int

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

final def ==(arg0: Any): Boolean

def H2ODistributionParam(name: String): H2ODistributionParam

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[_]): H2ODeepLearning.this.type

def clone(): AnyRef

def copy(extra: ParamMap): H2ODeepLearning.this.type

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

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

def defaultFileName: String

final val distribution: H2ODistributionParam

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

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

def getAllStringColumnsToCategorical(): Boolean

final def getClass(): Class[_]

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

def getDistribution(): DistributionFamily

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

def getEpochs(): Double

def getFeaturesCols(): Array[String]

def getH2ODoc(fieldName: String): String

def getHidden(): Array[Int]

def getKeepCrossValidationFoldAssignment(): Boolean

def getKeepCrossValidationPredictions(): Boolean

def getL1(): Double

def getL2(): Double

def getNfolds(): Int

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

def getParallelizeCrossValidation(): Boolean

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

def getParams: DeepLearningParameters

def getPredictionsCol(): String

def getReproducible(): Boolean

def getSeed(): Long

def getTrainRatio(): Double

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): BooleanParam

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

final def isInstanceOf[T0]: Boolean

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

def isTraceEnabled(): Boolean

final val keepCrossValidationFoldAssignment: BooleanParam

final val keepCrossValidationPredictions: BooleanParam

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 def ne(arg0: AnyRef): Boolean

final val nfolds: IntParam

final def notify(): Unit

final def notifyAll(): Unit

final val parallelizeCrossValidation: BooleanParam

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

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

def paramTag: ClassTag[DeepLearningParameters]

var parameters: DeepLearningParameters

lazy val params: Array[Param[_]]

final val predictionCol: Param[String]

final val ratio: DoubleParam

def save(path: String): Unit

def schemaTag: ClassTag[H2O_SCHEMA]

final val seed: LongParam

final def set(paramPair: ParamPair[_]): H2ODeepLearning.this.type

final def set(param: String, value: Any): H2ODeepLearning.this.type

final def set[T](param: Param[T], value: T): H2ODeepLearning.this.type

def setAllStringColumnsToCategorical(transform: Boolean): H2ODeepLearning.this.type

final def setDefault(paramPairs: ParamPair[_]*): H2ODeepLearning.this.type

final def setDefault[T](param: Param[T], value: T): H2ODeepLearning.this.type

def setDistribution(value: DistributionFamily): H2ODeepLearning.this.type

def setEpochs(value: Double): H2ODeepLearning.this.type

def setFeaturesCol(first: String): H2ODeepLearning.this.type

def setFeaturesCols(cols: Array[String]): H2ODeepLearning.this.type

def setFeaturesCols(first: String, others: String*): H2ODeepLearning.this.type

def setHidden(value: Array[Int]): H2ODeepLearning.this.type

def setKeepCrossValidationFoldAssignment(value: Boolean): H2ODeepLearning.this.type

def setKeepCrossValidationPredictions(value: Boolean): H2ODeepLearning.this.type

def setL1(value: Double): H2ODeepLearning.this.type

def setL2(value: Double): H2ODeepLearning.this.type

def setNfolds(value: Int): H2ODeepLearning.this.type

def setParallelizeCrossValidation(value: Boolean): H2ODeepLearning.this.type

def setParams(params: DeepLearningParameters): Unit

def setPredictionsCol(value: String): H2ODeepLearning.this.type

def setReproducible(value: Boolean): H2ODeepLearning.this.type

def setSeed(value: Long): H2ODeepLearning.this.type

def setTrainRatio(value: Double): H2ODeepLearning.this.type

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 trainModel(params: DeepLearningParameters): H2OMOJOModel

def transformSchema(schema: StructType): StructType

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

val uid: String

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

def write: MLWriter

def validateParams(): Unit