Hello, I found it useful to implement the Hadamard Product <https://en.wikipedia.org/wiki/Hadamard_product_%28matrices%29http://> as a VectorTransformer. It can be applied to scale (by a constant) a certain dimension (column) of the data set.
Since I've already implemented it and am using it, I thought I'd see if there's interest in this feature going in as Experimental. I'm not sold on the name 'Weighter', either. Here's the current branch with the work (docs, impl, tests). <https://github.com/ogeagla/spark/compare/spark-mllib-weighting> The implementation was heavily inspired by those of StandardScalerModel and Normalizer. Thanks Octavian -- View this message in context: http://apache-spark-developers-list.1001551.n3.nabble.com/Any-interest-in-weighting-VectorTransformer-which-does-component-wise-scaling-tp10265.html Sent from the Apache Spark Developers List mailing list archive at Nabble.com. --------------------------------------------------------------------- To unsubscribe, e-mail: dev-unsubscr...@spark.apache.org For additional commands, e-mail: dev-h...@spark.apache.org
