org.apache.spark.mllib.feature

PCAModel

class PCAModel extends VectorTransformer

Model fitted by PCA that can project vectors to a low-dimensional space using PCA.

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@Since( "1.4.0" )
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VectorTransformer, Serializable, Serializable, AnyRef, Any
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  1. PCAModel
  2. VectorTransformer
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  1. final def !=(arg0: AnyRef): Boolean

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

    Definition Classes
    Any
  3. final def ##(): Int

    Definition Classes
    AnyRef → Any
  4. final def ==(arg0: AnyRef): Boolean

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    AnyRef
  5. final def ==(arg0: Any): Boolean

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    Any
  6. final def asInstanceOf[T0]: T0

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  7. def clone(): AnyRef

    Attributes
    protected[java.lang]
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    @throws( ... )
  8. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  9. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any
  10. val explainedVariance: DenseVector

    Annotations
    @Since( "1.6.0" )
  11. def finalize(): Unit

    Attributes
    protected[java.lang]
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    @throws( classOf[java.lang.Throwable] )
  12. final def getClass(): Class[_]

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  13. def hashCode(): Int

    Definition Classes
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  14. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any
  15. val k: Int

    number of principal components.

    number of principal components.

    Annotations
    @Since( "1.4.0" )
  16. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  17. final def notify(): Unit

    Definition Classes
    AnyRef
  18. final def notifyAll(): Unit

    Definition Classes
    AnyRef
  19. val pc: DenseMatrix

    a principal components Matrix.

    a principal components Matrix. Each column is one principal component.

    Annotations
    @Since( "1.4.0" )
  20. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
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  21. def toString(): String

    Definition Classes
    AnyRef → Any
  22. def transform(vector: Vector): Vector

    Transform a vector by computed Principal Components.

    Transform a vector by computed Principal Components.

    vector

    vector to be transformed. Vector must be the same length as the source vectors given to PCA.fit().

    returns

    transformed vector. Vector will be of length k.

    Definition Classes
    PCAModelVectorTransformer
    Annotations
    @Since( "1.4.0" )
  23. def transform(data: JavaRDD[Vector]): JavaRDD[Vector]

    Applies transformation on a JavaRDD[Vector].

    Applies transformation on a JavaRDD[Vector].

    data

    JavaRDD[Vector] to be transformed.

    returns

    transformed JavaRDD[Vector].

    Definition Classes
    VectorTransformer
    Annotations
    @Since( "1.1.0" )
  24. def transform(data: RDD[Vector]): RDD[Vector]

    Applies transformation on an RDD[Vector].

    Applies transformation on an RDD[Vector].

    data

    RDD[Vector] to be transformed.

    returns

    transformed RDD[Vector].

    Definition Classes
    VectorTransformer
    Annotations
    @Since( "1.1.0" )
  25. final def wait(): Unit

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    @throws( ... )
  26. final def wait(arg0: Long, arg1: Int): Unit

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    @throws( ... )
  27. final def wait(arg0: Long): Unit

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    @throws( ... )

Inherited from VectorTransformer

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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