org.apache.spark.mllib.feature

PCA

class PCA extends AnyRef

A feature transformer that projects vectors to a low-dimensional space using PCA.

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Instance Constructors

  1. new PCA(k: Int)

    k

    number of principal components

Value Members

  1. final def !=(arg0: AnyRef): Boolean

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  2. final def !=(arg0: Any): Boolean

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  3. final def ##(): Int

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  7. def clone(): AnyRef

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

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  10. def finalize(): Unit

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  11. def fit(sources: JavaRDD[Vector]): PCAModel

    Java-friendly version of fit()

  12. def fit(sources: RDD[Vector]): PCAModel

    Computes a PCAModel that contains the principal components of the input vectors.

    Computes a PCAModel that contains the principal components of the input vectors.

    sources

    source vectors

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

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  14. def hashCode(): Int

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  15. final def isInstanceOf[T0]: Boolean

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  16. val k: Int

    number of principal components

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

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  18. final def notify(): Unit

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  19. final def notifyAll(): Unit

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

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  21. def toString(): String

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

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

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