dk.bayes.clustergraph.em

DataSet

Related Docs: object DataSet | package em

case class DataSet(variableIds: Array[Int], samples: Array[Array[Int]]) extends Product with Serializable

Represents data samples, which are used for learning parameters of Bayesian Network.

variableIds

Defines the order of variables in a single sample

samples

Single sample contains values for all variables in a Bayesian Network

Use -1 to encode unknown value for a variable.

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Instance Constructors

  1. new DataSet(variableIds: Array[Int], samples: Array[Array[Int]])

    variableIds

    Defines the order of variables in a single sample

    samples

    Single sample contains values for all variables in a Bayesian Network

    Use -1 to encode unknown value for a variable.

Value Members

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

    Definition Classes
    AnyRef → Any

  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 finalize(): Unit

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

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  9. final def isInstanceOf[T0]: Boolean

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

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  11. final def notify(): Unit

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  12. final def notifyAll(): Unit

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  13. val samples: Array[Array[Int]]

    Single sample contains values for all variables in a Bayesian Network

    Single sample contains values for all variables in a Bayesian Network

    Use -1 to encode unknown value for a variable.

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

    Definition Classes
    AnyRef

  15. val variableIds: Array[Int]

    Defines the order of variables in a single sample

  16. final def wait(): Unit

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    @throws( ... )

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

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

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