Packages

final class EMLDAOptimizer extends LDAOptimizer

Optimizer for EM algorithm which stores data + parameter graph, plus algorithm parameters.

Currently, the underlying implementation uses Expectation-Maximization (EM), implemented according to the Asuncion et al. (2009) paper referenced below.

References:

  • Original LDA paper (journal version): Blei, Ng, and Jordan. "Latent Dirichlet Allocation." JMLR, 2003.
    • This class implements their "smoothed" LDA model.
  • Paper which clearly explains several algorithms, including EM: Asuncion, Welling, Smyth, and Teh. "On Smoothing and Inference for Topic Models." UAI, 2009.
Annotations
@Since( "1.4.0" )
Source
LDAOptimizer.scala
Linear Supertypes
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. EMLDAOptimizer
  2. LDAOptimizer
  3. AnyRef
  4. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

Instance Constructors

  1. new EMLDAOptimizer()

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  5. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  6. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  7. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  8. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  9. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  10. def getKeepLastCheckpoint: Boolean

    If using checkpointing, this indicates whether to keep the last checkpoint (vs clean up).

    If using checkpointing, this indicates whether to keep the last checkpoint (vs clean up).

    Annotations
    @Since( "2.0.0" )
  11. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  12. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  13. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  14. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  15. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  16. def setKeepLastCheckpoint(keepLastCheckpoint: Boolean): EMLDAOptimizer.this.type

    If using checkpointing, this indicates whether to keep the last checkpoint (vs clean up).

    If using checkpointing, this indicates whether to keep the last checkpoint (vs clean up). Deleting the checkpoint can cause failures if a data partition is lost, so set this bit with care.

    Default: true

    Annotations
    @Since( "2.0.0" )
    Note

    Checkpoints will be cleaned up via reference counting, regardless.

  17. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  18. def toString(): String
    Definition Classes
    AnyRef → Any
  19. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  20. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  21. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()

Inherited from LDAOptimizer

Inherited from AnyRef

Inherited from Any

Ungrouped