ElementwiseProduct¶
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class
pyspark.mllib.feature.ElementwiseProduct(scalingVector: pyspark.mllib.linalg.Vector)[source]¶ Scales each column of the vector, with the supplied weight vector. i.e the elementwise product.
New in version 1.5.0.
Examples
>>> weight = Vectors.dense([1.0, 2.0, 3.0]) >>> eprod = ElementwiseProduct(weight) >>> a = Vectors.dense([2.0, 1.0, 3.0]) >>> eprod.transform(a) DenseVector([2.0, 2.0, 9.0]) >>> b = Vectors.dense([9.0, 3.0, 4.0]) >>> rdd = sc.parallelize([a, b]) >>> eprod.transform(rdd).collect() [DenseVector([2.0, 2.0, 9.0]), DenseVector([9.0, 6.0, 12.0])]
Methods
transform(vector)Computes the Hadamard product of the vector.
Methods Documentation
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transform(vector: Union[VectorLike, pyspark.rdd.RDD[VectorLike]]) → Union[pyspark.mllib.linalg.Vector, pyspark.rdd.RDD[pyspark.mllib.linalg.Vector]][source]¶ Computes the Hadamard product of the vector.
New in version 1.5.0.
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