Hey, Nice question, I'm interested to see what others have to say on this. I'd like to point out a couple of algorithmic points:
- If you are using regularisation the scaling /will/ lead to different results. - If you are using an iterative method to estimate something, (yes very vague but you get the gist), it can be very useful to know the data is scaled in a particular way, i.e., it can inform an initial guess for the iterative method. On a pedagogical note, it might be interesting to point out to your students that the act of choosing an scaling/transformation/preprocessing can be useful as a way of understanding your data better. Cheers, Alex On Tue, Jul 17, 2018 at 4:58 PM Michael Thompson < michael.thomp...@manukau.ac.nz> wrote: > Hi, > I seem to remember from classes that one effect of scaling / standardising > data was to get better results in any analysis. But what I'm seeing when I > study various explanations on scaling is that we get exactly the same > results, just that when we look at standardised data it's easier to see > proportionate effects. > This is all very well for the data scientist to further investigate, but > from a practical point of view, (especially IF it doesn't improve the > accuracy of the result) surely it adds complication to 'telling the story' > of the model to non-DS people? > So, is scaling a technique for the DS to use to find effects, while > eventually delivering a non-scaled version to the users? > I'd like to be able to give the true story to my students, not some fairy > story based on my misunderstanding. Hope you can help with this. > Michael > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
