Hmm... Scaler and Scalar are very close together both in terms of pronunciation and spelling - and I wouldn't want to create confusion between the two. Further - this operation (elementwise multiplication by a static vector) is general enough that maybe it should have a more general name?
On Tue, Jan 27, 2015 at 7:54 AM, Xiangrui Meng <men...@gmail.com> wrote: > I would call it Scaler. You might want to add it to the spark.ml pipieline > api. Please check the spark.ml.HashingTF implementation. Note that this > should handle sparse vectors efficiently. > > Hadamard and FFTs are quite useful. If you are intetested, make sure that > we call an FFT libary that is license-compatible with Apache. > > -Xiangrui > On Jan 24, 2015 8:27 AM, "Octavian Geagla" <ogea...@gmail.com> wrote: > > > 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 > > > > >
