org.apache.predictionio.controller

Engine

object Engine extends Serializable

This object contains concrete implementation for some methods of the Engine class.

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Type Members

  1. class DataSourceMap[TD, EI, Q, A] extends AnyRef

    Helper class to accept either a single data source, or a map of data sources, with a companion object providing implicit conversions, so using this class directly is not necessary.

  2. class PreparatorMap[TD, PD] extends AnyRef

    Helper class to accept either a single preparator, or a map of preparators, with a companion object providing implicit conversions, so using this class directly is not necessary.

  3. class ServingMap[Q, P] extends AnyRef

    Helper class to accept either a single serving, or a map of serving, with a companion object providing implicit conversions, so using this class directly is not necessary.

Value Members

  1. final def !=(arg0: AnyRef): Boolean

    Definition Classes
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  2. final def !=(arg0: Any): Boolean

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  3. final def ##(): Int

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  4. final def ==(arg0: AnyRef): Boolean

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  5. final def ==(arg0: Any): Boolean

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  6. object DataSourceMap

    Companion object providing implicit conversions, so using this directly is not necessary.

  7. object PreparatorMap

    Companion object providing implicit conversions, so using this directly is not necessary.

  8. object ServingMap

    Companion object providing implicit conversions, so using this directly is not necessary.

  9. def apply[TD, EI, PD, Q, P, A](dataSourceMap: DataSourceMap[TD, EI, Q, A], preparatorMap: PreparatorMap[TD, PD], algorithmClassMap: Map[String, Class[_ <: BaseAlgorithm[PD, _, Q, P]]], servingMap: ServingMap[Q, P]): Engine[TD, EI, PD, Q, P, A]

    Convenient method for returning an instance of Engine.

    Convenient method for returning an instance of Engine.

    TD

    Training data class

    EI

    Evaluation information class

    PD

    Prepared data class

    Q

    Input query class

    P

    Predicted result class

    A

    Actual result class

    dataSourceMap

    Accepts either an instance of Class of the data source, or a Map of data source classes (implicitly converted to DataSourceMap.

    preparatorMap

    Accepts either an instance of Class of the preparator, or a Map of preparator classes (implicitly converted to PreparatorMap.

    algorithmClassMap

    Accepts a Map of algorithm classes.

    servingMap

    Accepts either an instance of Class of the serving, or a Map of serving classes (implicitly converted to ServingMap.

    returns

    An instance of Engine

  10. final def asInstanceOf[T0]: T0

    Definition Classes
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  11. def clone(): AnyRef

    Attributes
    protected[java.lang]
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    @throws( ... )
  12. final def eq(arg0: AnyRef): Boolean

    Definition Classes
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  13. def equals(arg0: Any): Boolean

    Definition Classes
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  14. def eval[TD, PD, Q, P, A, EI](sc: SparkContext, dataSource: BaseDataSource[TD, EI, Q, A], preparator: BasePreparator[TD, PD], algorithmList: Seq[BaseAlgorithm[PD, _, Q, P]], serving: BaseServing[Q, P]): Seq[(EI, RDD[(Q, P, A)])]

    Provides concrete implementation of evaluation for Engine.

    Provides concrete implementation of evaluation for Engine.

    TD

    Training data class

    PD

    Prepared data class

    Q

    Input query class

    P

    Predicted result class

    A

    Actual result class

    EI

    Evaluation information class

    sc

    An instance of SparkContext

    dataSource

    An instance of data source

    preparator

    An instance of preparator

    algorithmList

    A list of algorithm instances

    serving

    An instance of serving

    returns

    A list of evaluation information, RDD of query, predicted result, and actual result tuple tuple.

  15. def finalize(): Unit

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    @throws( classOf[java.lang.Throwable] )
  16. final def getClass(): Class[_]

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  17. def hashCode(): Int

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  18. final def isInstanceOf[T0]: Boolean

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  19. final def ne(arg0: AnyRef): Boolean

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  20. final def notify(): Unit

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  21. final def notifyAll(): Unit

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

    Definition Classes
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  23. def toString(): String

    Definition Classes
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  24. def train[TD, PD, Q](sc: SparkContext, dataSource: BaseDataSource[TD, _, Q, _], preparator: BasePreparator[TD, PD], algorithmList: Seq[BaseAlgorithm[PD, _, Q, _]], params: WorkflowParams): Seq[Any]

    Provides concrete implementation of training for Engine.

    Provides concrete implementation of training for Engine.

    TD

    Training data class

    PD

    Prepared data class

    Q

    Input query class

    sc

    An instance of SparkContext

    dataSource

    An instance of data source

    preparator

    An instance of preparator

    algorithmList

    A list of algorithm instances

    params

    An instance of WorkflowParams that controls the training process.

    returns

    A list of trained models

  25. final def wait(): Unit

    Definition Classes
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    @throws( ... )
  26. final def wait(arg0: Long, arg1: Int): Unit

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    @throws( ... )
  27. final def wait(arg0: Long): Unit

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    @throws( ... )

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

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