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From Eric Barnhill <>
Subject [statistics-regression] Proposed Regression class/method structure
Date Tue, 22 Oct 2019 19:49:41 GMT
I propose the following class structure for commons-statistics-regression.

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.

Under the hood I would use the available implementations in commons-math to
get up and running, and worry about improving them later.

Feedback appreciated,

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