DLClassifier

final def !=(arg0: Any): Boolean

final def ##(): Int

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

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

final val batchShape: Param[Array[Int]]

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

def clone(): AnyRef

def copy(extra: ParamMap): DLClassifier[T]

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

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

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

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

final def getBatchSize: Array[Int]

get the batch shape

final def getClass(): Class[_]

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

final def getInputCol: String

final def getModel: Module[T]

get the model

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

final def getOutputCol: String

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

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

def hasParam(paramName: String): Boolean

def hashCode(): Int

def initializeLogIfNecessary(isInterpreter: Boolean): Unit

final val inputCol: Param[String]

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

final def isInstanceOf[T0]: Boolean

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

def isTraceEnabled(): Boolean

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

final val modelTrain: Param[Module[T]]

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

final val outputCol: Param[String]

lazy val params: Array[Param[_]]

def process(dataset: DataFrame): DataFrame

Perform a prediction on inputCol, and write result to the outputCol.

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

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

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

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

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

def setInputCol(inputColName: String): DLClassifier.this.type

Set the input column name

def setOutputCol(outputColName: String): DLClassifier.this.type

Set the output column name, should not existed in the DataFrame.

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

def toString(): String

def transform(dataset: Dataset[_]): DataFrame

def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame

def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame

def transformSchema(schema: StructType): StructType

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

val uid: String

def validateParameters(): Unit

final def wait(): Unit

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

final def wait(arg0: Long): Unit

def validateParams(): Unit