Class

net.sansa_stack.ml.spark.kge.linkprediction.models

DistMult

Related Doc: package models

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class DistMult extends Models

DistMult: diagonal bilinear model ---------------------------------

Yang, Bishan, et al. Learning multi-relational semantics using neural-embedding models." arXiv:1411.4072 (2014).

Created by lpfgarcia on 20/11/2017.

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Instance Constructors

  1. new DistMult(train: Dataset[IntegerTriples], ne: Int, nr: Int, batch: Int, k: Int, sk: SparkSession)

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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. def L1(vec: Tensor[Float]): Float

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  5. def L2(vec: Tensor[Float]): Float

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  6. val Ne: Int

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  7. val Nr: Int

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  8. final def asInstanceOf[T0]: T0

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  9. def clone(): AnyRef

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  10. def dist(data: Dataset[IntegerTriples]): Float

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  11. var e: Tensor[Float]

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  12. val epochs: Int

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

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  14. def equals(arg0: Any): Boolean

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  15. def finalize(): Unit

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

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  17. def hashCode(): Int

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  18. def initialize(size: Int): Tensor[Float]

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  19. final def isInstanceOf[T0]: Boolean

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

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  21. def negative(data: Dataset[IntegerTriples]): Dataset[IntegerTriples]

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  22. def normalize(data: Tensor[Float]): Tensor[Float]

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  23. final def notify(): Unit

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  24. final def notifyAll(): Unit

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  25. var opt: Adam[Float]

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  26. var r: Tensor[Float]

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  27. val rate: Float

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  28. def run(): Unit

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  29. val seed: Random

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  30. def subset(data: Dataset[IntegerTriples]): Dataset[IntegerTriples]

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

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  32. def toString(): String

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  33. def tuple(aux: IntegerTriples): IntegerTriples

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  34. final def wait(): Unit

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

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

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