BaseEngine

abstract def eval(sc: SparkContext, engineParams: EngineParams, params: WorkflowParams): Seq[(EI, RDD[(Q, P, A)])]

:: DeveloperApi :: Implement this method so that io.prediction.controller.Evaluation can use this method to generate inputs for io.prediction.controller.Metric.

abstract def train(sc: SparkContext, engineParams: EngineParams, engineInstanceId: String, params: WorkflowParams): Seq[Any]

:: DeveloperApi :: Implement this method so that training this engine would return a list of models.

final def !=(arg0: AnyRef): Boolean

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: AnyRef): Boolean

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

def batchEval(sc: SparkContext, engineParamsList: Seq[EngineParams], params: WorkflowParams): Seq[(EngineParams, Seq[(EI, RDD[(Q, P, A)])])]

:: DeveloperApi :: Override this method to further optimize the process that runs multiple evaluations (during tuning, for example).

def clone(): AnyRef

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def finalize(): Unit

final def getClass(): Class[_]

def hashCode(): Int

final def isInstanceOf[T0]: Boolean

def jValueToEngineParams(variantJson: JValue, jsonExtractor: JsonExtractorOption): EngineParams

:: DeveloperApi :: Implement this method to convert a JValue (read from an engine variant JSON file) to an instance of EngineParams.

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

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

def toString(): String

final def wait(): Unit

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

final def wait(arg0: Long): Unit