Object/Class

org.apache.spark.mllib.clustering

DistributedLDAModel

Related Docs: class DistributedLDAModel | package clustering

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object DistributedLDAModel extends Loader[DistributedLDAModel]

Distributed model fitted by LDA. This type of model is currently only produced by Expectation-Maximization (EM).

This model stores the inferred topics, the full training dataset, and the topic distribution for each training document.

Annotations
@Since( "1.5.0" )
Source
LDAModel.scala
Linear Supertypes
Loader[DistributedLDAModel], AnyRef, Any
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  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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  8. def finalize(): Unit

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

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  10. def hashCode(): Int

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  11. final def isInstanceOf[T0]: Boolean

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  12. def load(sc: SparkContext, path: String): DistributedLDAModel

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    Load a model from the given path.

    Load a model from the given path.

    The model should have been saved by Saveable.save.

    sc

    Spark context used for loading model files.

    path

    Path specifying the directory to which the model was saved.

    returns

    Model instance

    Definition Classes
    DistributedLDAModel → Loader
    Annotations
    @Since( "1.5.0" )

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

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  14. final def notify(): Unit

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  15. final def notifyAll(): Unit

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

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  17. def toString(): String

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  18. final def wait(): Unit

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

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

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Inherited from Loader[DistributedLDAModel]

Inherited from AnyRef

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