KMeansRunner

Value Members

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

   

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2. final def ##(): Int

   

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

   

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4. final def asInstanceOf[T0]: T0

   

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5. def clone(): AnyRef

   

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

   

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7. def equals(arg0: Any): Boolean

   

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8. def finalize(): Unit

   

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

   

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10. def hashCode(): Int

    

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11. final def isInstanceOf[T0]: Boolean

    

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

    

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13. final def notify(): Unit

    

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14. final def notifyAll(): Unit

    

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15. def predict(conf: Configuration): Unit

    

    Using a model to predict with unobserved samples

    Using a model to predict with unobserved samples

    Definition Classes

    KMeansRunner → MLRunner

16. final def predict(conf: Configuration, model: MLModel, taskClass: Class[_ <: BaseTask[_, _, _]]): Unit

    

    Default predict method with standard predict process.

    Default predict method with standard predict process. Don't try to override this Method.

    Attributes

    protected

    Definition Classes

    MLRunner

17. def submit(conf: Configuration): Unit

    

    Definition Classes

    MLRunner → AppSubmitter

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

    

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19. def toString(): String

    

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20. def train(conf: Configuration): Unit

    

    Training job to obtain a model

    Training job to obtain a model

    Definition Classes

    KMeansRunner → MLRunner

21. final def train(conf: Configuration, model: MLModel, taskClass: Class[_ <: BaseTask[_, _, _]]): Unit

    

    Default train method with standard training process.

    Default train method with standard training process. Don't Override this method.

    Attributes

    protected

    Definition Classes

    MLRunner

22. final def wait(): Unit

    

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

    

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

    

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