H2ODeepLearning

final def !=(arg0: Any): Boolean

final def ##(): Int

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

final def ==(arg0: Any): Boolean

def allStringVecToCategorical(hf: H2OFrame): H2OFrame

final def asInstanceOf[T0]: T0

def booleanParam(name: 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

def doc(fieldName: String): String

def doubleParam(name: String): DoubleParam

final val epochs: DoubleParam

All parameters should be set here along with their documentation and explained default values

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

def finalize(): Unit

def fit(dataset: Dataset[_]): H2ODeepLearningModel

def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[H2ODeepLearningModel]

def fit(dataset: Dataset[_], paramMap: ParamMap): H2ODeepLearningModel

def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): H2ODeepLearningModel

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

final def getClass(): Class[_]

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

def getEpochs: Double

def getHidden: Array[Int]

def getL1: Double

def getL2: Double

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

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

def getParams: DeepLearningParameters

def getResponseColumn: String

def getTrainKey: String

def getValidKey: String

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

def hasParam(paramName: String): Boolean

def hashCode(): Int

final val hidden: IntArrayParam

def initializeLogIfNecessary(isInterpreter: Boolean): Unit

def intParam(name: String): IntParam

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

final def isInstanceOf[T0]: Boolean

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

def isTraceEnabled(): Boolean

final val l1: DoubleParam

final val l2: DoubleParam

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): LongParam

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

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

def paramTag: ClassTag[DeepLearningParameters]

var parameters: DeepLearningParameters

lazy val params: Array[Param[_]]

final val responseColumn: Param[String]

def save(path: String): Unit

def schemaTag: ClassTag[H2O_SCHEMA]

final def set[T](param: Param[T], value: T)(f: ⇒ Unit): SELF

Set the param and execute custom piece of code

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

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

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

def setEpochs(value: Double): SELF

def setHidden(value: Array[Int]): SELF

def setL1(value: Double): SELF

def setL2(value: Double): SELF

def setParams(params: DeepLearningParameters): Unit

def setResponseColumn(value: String): SELF

def setTrainKey(value: Key[Frame]): SELF

def setTrainKey(value: String): SELF

def setValidKey(value: Key[Frame]): SELF

def setValidKey(value: String): SELF

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

def toString(): String

final val trainKey: H2OKeyParam[Frame]

def trainModel(params: DeepLearningParameters): H2ODeepLearningModel

def transformSchema(schema: StructType): StructType

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

val uid: String

final val validKey: H2OKeyParam[Frame]

final def wait(): Unit

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

final def wait(arg0: Long): Unit

def write: MLWriter

def validateParams(): Unit