Class/Object

net.sansa_stack.ml.spark.outliers.anomalydetection

AnomalyWithHashingTF

Related Docs: object AnomalyWithHashingTF | package anomalydetection

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class AnomalyWithHashingTF extends Serializable

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  1. AnomalyWithHashingTF
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Instance Constructors

  1. new AnomalyWithHashingTF(nTriplesRDD: RDD[Triple], objList: List[String], triplesType: List[String], JSimThreshold: Double, listSuperType: List[String], sparkSession: SparkSession, hypernym: String, numPartition: Int)

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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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    @throws( classOf[java.lang.Throwable] )

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

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  10. def getHyp(): RDD[Triple]

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  11. def getObjectList(): RDD[Triple]

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  12. def hashCode(): Int

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  13. def iqr2(cluster: Seq[(String, String, AnyRef)], anomalyListLimit: Int): Seq[(String, String, AnyRef)]

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  14. final def isInstanceOf[T0]: Boolean

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  15. def jSimilarity(TriplesWithNumericLiteral: RDD[Triple], xse: RDD[(String, String)], rdfTypeDBwiki: RDD[(String, HashSet[String])], mapSubWithTriples: RDD[(String, Set[(String, String, AnyRef)])]): RDD[Set[(String, String, AnyRef)]]

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

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  17. final def notify(): Unit

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  18. final def notifyAll(): Unit

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  19. def propClustering(triplesWithNumericLiteral: RDD[Triple]): RDD[(String, Set[(String, String, AnyRef)])]

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  20. def propwithsubject(a: RDD[Triple]): RDD[(String, String)]

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  21. def rdfType(getHypernym: RDD[Triple]): RDD[(String, HashSet[String])]

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  22. def run(): RDD[Set[(String, String, AnyRef)]]

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

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  24. def toString(): String

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  25. def triplesWithNumericLit(objLit: RDD[Triple]): RDD[Triple]

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  26. final def wait(): Unit

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

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

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