Steven D'Aprano <steve+pyt...@pearwood.info> added the comment: > The ML world has collapsed on the terms X and y. (With that > capitalization).
I just googled for "ML linear regression" and there is no consistency in either the variable used or the parameters. But most seem to use lowercase x,y. Out of the top 6 links I checked, only one seems to use X,y and even there the y has a hat (circumflex) on it: X,ŷ. More importantly, the ML community has no consistency about the parameters either. I see: y = B0 + B1*x ŷ = X W + b y = a_0 + a_1 * x y = m x + b y = θ1 + θ2 x y = b0 + b1 x I'm going to give the URLs since the search page results are not reproducable from person to person. See below. The bottom line here is that I don't think the ML community is going to give us much guidence here. And it's probably not our target user base either, which is more aimed at high school and undergraduate users of basic level statistics, not ML algorithms. https://www.geeksforgeeks.org/ml-linear-regression/ https://ml-cheatsheet.readthedocs.io/en/latest/linear_regression.html https://towardsdatascience.com/introduction-to-machine-learning-algorithms-linear-regression-14c4e325882a https://machinelearningmastery.com/linear-regression-for-machine-learning/ https://www.analytixlabs.co.in/blog/linear-regression-machine-learning/ https://madewithml.com/courses/basics/linear-regression/ ---------- _______________________________________ Python tracker <rep...@bugs.python.org> <https://bugs.python.org/issue44151> _______________________________________ _______________________________________________ Python-bugs-list mailing list Unsubscribe: https://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
