Packages

c

scalation.analytics

NMFactorization

class NMFactorization extends Reducer

The NMFactorization class factors a matrix 'x' into two non negative matrices 'w' and 'h' such that 'x = wh' approximately.

See also

en.wikipedia.org/wiki/Non-negative_matrix_factorization

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Instance Constructors

  1. new NMFactorization(x: MatriD, loops: Int = 10, r: Int = 0)

    x

    the matrix to be factored

    loops

    the number of iterations before checking the termination condition

    r

    factor the m-by-n matrix 'x' in to two factors: an m-by-r and r-by-n matrix

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
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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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    protected[lang]
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    @throws( ... ) @native() @HotSpotIntrinsicCandidate()
  6. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  7. def equals(arg0: Any): Boolean
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    AnyRef → Any
  8. def factorReduce(): (MatrixD, MatrixD)

    Factor and reduce the original matrix 'x' into left 'w' and right 'h' matrices by iteratively calling the 'update' method until the difference between 'x' and its reduced approximation 'xr = w * h' is sufficiently small.

    Factor and reduce the original matrix 'x' into left 'w' and right 'h' matrices by iteratively calling the 'update' method until the difference between 'x' and its reduced approximation 'xr = w * h' is sufficiently small.

    Definition Classes
    NMFactorizationReducer
  9. final def getClass(): Class[_]
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    @native() @HotSpotIntrinsicCandidate()
  10. def hashCode(): Int
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    @native() @HotSpotIntrinsicCandidate()
  11. final def isInstanceOf[T0]: Boolean
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  12. final def ne(arg0: AnyRef): Boolean
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  13. final def notify(): Unit
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    @native() @HotSpotIntrinsicCandidate()
  14. final def notifyAll(): Unit
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    @native() @HotSpotIntrinsicCandidate()
  15. var r: Int
  16. def recover(): MatriD

    Approximately recover the original matrix.

    Approximately recover the original matrix. The new matrix will have the same dimensionality, but will have some lose of information.

    Definition Classes
    NMFactorizationReducer
  17. def reduce(): MatriD

    Reduce the original data matrix by producing a lower dimensionality matrix that maintains most of the descriptive power of the original matrix.

    Reduce the original data matrix by producing a lower dimensionality matrix that maintains most of the descriptive power of the original matrix.

    Definition Classes
    NMFactorizationReducer
  18. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
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  19. def toString(): String
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  20. final def wait(arg0: Long, arg1: Int): Unit
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    @throws( ... )
  21. final def wait(arg0: Long): Unit
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  22. final def wait(): Unit
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    @throws( ... )

Deprecated Value Members

  1. def finalize(): Unit
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    protected[lang]
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    @throws( classOf[java.lang.Throwable] ) @Deprecated
    Deprecated

Inherited from Reducer

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