org.apache.spark.streamdm.core

ClassificationModel

trait ClassificationModel extends Model

A ClassificationModel trait defines the needed operations on any classification Model. It provides methods for updating the model and for predicting the label of a given Instance

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LinearModel
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  1. abstract type T <: Model

    Definition Classes
    Model

Abstract Value Members

  1. abstract def predict(instance: Example): Double

  2. abstract def prob(instance: Example): Double

    Computes the probability for a given label class, given the current Model

    Computes the probability for a given label class, given the current Model

    instance

    the Instance which needs a class predicted

    returns

    the predicted probability

  3. abstract def update(change: Example): T

    Update the model, depending on the Instance given for training.

    Update the model, depending on the Instance given for training.

    change

    the example based on which the Model is updated

    returns

    the updated Model

    Definition Classes
    Model

Concrete Value Members

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

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  2. 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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  10. def finalize(): Unit

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

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

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

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

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Inherited from Model

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