class PCAModel extends VectorTransformer
Model fitted by PCA that can project vectors to a low-dimensional space using PCA.
- Annotations
- @Since( "1.4.0" )
- Source
- PCA.scala
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- PCAModel
- VectorTransformer
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Value Members
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val
explainedVariance: DenseVector
- Annotations
- @Since( "1.6.0" )
-
val
k: Int
- Annotations
- @Since( "1.4.0" )
-
val
pc: DenseMatrix
- Annotations
- @Since( "1.4.0" )
-
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
- PCAModel → VectorTransformer
- Annotations
- @Since( "1.4.0" )
-
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" )
-
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" )