Packages

final case class MarkovChain[A](data: Data[A]) extends Product with Serializable

Linear Supertypes
Serializable, Serializable, Product, Equals, AnyRef, Any
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  1. MarkovChain
  2. Serializable
  3. Serializable
  4. Product
  5. Equals
  6. AnyRef
  7. Any
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Visibility
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Instance Constructors

  1. new MarkovChain(data: Data[A])

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. def +(pair: (A, A)): MarkovChain[A]

    Alias for put

  4. def ++(markovChain: MarkovChain[A]): MarkovChain[A]

    Alias for join

  5. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  6. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  7. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  8. val data: Data[A]
  9. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  10. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  11. def fromSeq(xs: Seq[A]): MarkovChain[A]

    Create chain from sequence of items.

    Create chain from sequence of items. Relationship will be created by making connections between each consecutive item.

  12. def get(a: A): Option[A]

    Get single item with highest probability value.

  13. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  14. def getRandomSeq(atMost: Int)(implicit rand: RandLike): Vector[A]

    Get sequence of elements selecting highest probability elements starting with random element.

  15. def getRandomSeqWithProb(atMost: Int)(implicit rand: RandLike): Vector[A]

    Get sequence of elements using probability distribution starting with random element.

  16. def getSeq(a: A, atMost: Int): Vector[A]

    Get sequence of elements using highest probability value.

  17. def getSeqWithProb(a: A, atMost: Int)(implicit rand: RandLike): Vector[A]

    Get sequence of elements using probability distribution.

  18. def getTop(a: A, num: Int): List[A]

    Get top N items with highest probability value.

  19. def getWithProb(a: A)(implicit rand: RandLike): Option[A]

    Get single item from probability distribution.

  20. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  21. def join(that: MarkovChain[A]): MarkovChain[A]

    Combine two instances of MarkovChain

  22. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  23. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  24. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  25. def put(a: A, b: A): MarkovChain[A]

    Add single element to the chain

  26. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  27. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  28. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  29. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from AnyRef

Inherited from Any

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