class Normalizer extends VectorTransformer
Normalizes samples individually to unit Lp norm
For any 1 <= p < Double.PositiveInfinity, normalizes samples using sum(abs(vector).p)(1/p) as norm.
For p = Double.PositiveInfinity, max(abs(vector)) will be used as norm for normalization.
- Annotations
- @Since( "1.1.0" )
- Source
- Normalizer.scala
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- Normalizer
- VectorTransformer
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def
transform(vector: Vector): Vector
Applies unit length normalization on a vector.
Applies unit length normalization on a vector.
- vector
vector to be normalized.
- returns
normalized vector. If the norm of the input is zero, it will return the input vector.
- Definition Classes
- Normalizer → VectorTransformer
- Annotations
- @Since( "1.1.0" )
-
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" )