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From Eric Barnhill <ericbarnh...@gmail.com>
Subject Re: [statistics-regression] Proposed Regression class/method structure
Date Tue, 22 Oct 2019 23:15:37 GMT
Here is a link to the picture

https://imgur.com/a/9jjoOGB

On Tue, Oct 22, 2019 at 4:13 PM Gilles Sadowski <gilleseran@gmail.com>
wrote:

> Hello.
>
> Le mar. 22 oct. 2019 à 21:50, Eric Barnhill <ericbarnhill@gmail.com> a
> écrit :
> >
> > I propose the following class structure for
> commons-statistics-regression.
>
> Which?
> [Attachment was probably stripped: such should go to a JIRA report.]
>
> > The interface carried over from commons-math is more of an academic
> approach to thinking about regression. For rebooting the library (and I
> hinted at this when I wrote the tickets for summer of code) I was hoping to
> emulate widespread tools like R and scikit-learn, and consider that
> "machine learning" is an increasingly popular use of regression. This
> proposed structure creates an interface that is not the same as, but will
> be very friendly to, anyone coming from R or scikit-learn, or similar tools
> in JavaScript.
> >
> > There are of course many ways I can see to elaborate this scheme, say
> using RegressionResult objects and so forth. But Matrices paired with a
> double[], returning a double[] of coefficients or predictions, are likely
> to be the most common use cases and should be plenty to get started.
>
> Commenting perhaps too early (not seeing the proposed design), but we
> broadly
> discussed that the linear algebra API is not easy to get right, and once
> we "get
> started", the trend is to be stuck with it for ages (related issues
> are among the
> oldest unresolved ones in CM).
>
> > Under the hood I would use the available implementations in commons-math
> to get up and running, and worry about improving them later.
>
> Do you mean port from, or depend on, CM?
>
> Regards,
> Gilles
>
> >
> > Feedback appreciated,
> > Eric
>
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