IFSPersistentModel

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

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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. final def asInstanceOf[T0]: T0

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7. def clone(): AnyRef

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8. final def eq(arg0: AnyRef): Boolean

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9. def equals(arg0: Any): Boolean

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10. def finalize(): Unit

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11. final def getClass(): Class[_]

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12. def hashCode(): Int

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13. final def isInstanceOf[T0]: Boolean

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

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15. final def notify(): Unit

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16. final def notifyAll(): Unit

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17. def save(id: String, params: AP, sc: SparkContext): Boolean

    Save the model to some persistent storage.

    Save the model to some persistent storage.

    This method should return true if the model has been saved successfully so that PredictionIO knows that it can be restored later during deployment. This method should return false if the model cannot be saved (or should not be saved due to configuration) so that PredictionIO will re-train the model during deployment. All arguments of this method are provided by automatically by PredictionIO.

    id

    ID of the run that trained this model.

    params

    Algorithm parameters that were used to train this model.

    sc

    An Apache Spark context.

    Definition Classes

    LocalFileSystemPersistentModel → PersistentModel

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

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19. def toString(): String

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20. final def wait(): Unit

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

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22. final def wait(arg0: Long): Unit

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