And when I mean testing it, I mean writing tests that live with the code so that they can be re-executed, and so that someone else can see what your tests assert about your code's correctness.
On 5 June 2017 at 11:52, Joel Nothman <joel.noth...@gmail.com> wrote: > Hi Rain, > > I would suggest that you start by documenting what your code is meant to > do (the structure of the Korjus et al paper makes it pretty difficult to > even determine what this technique is, for you to then not to describe it > in your own words in your repository), testing it with diverse inputs and > ensuring that it is correct. At a glance I can see at least two sources of > bugs, and some API design choices which I think could be improved. > > Cheers, > > Joel > > On 5 June 2017 at 07:04, Rain Vagel <rain.va...@gmail.com> wrote: > >> Hey, >> >> I am a bachelor’s student and for my thesis I implemented a cross-testing >> function in a scikit-learn compatible way and published it on Github. The >> paper on which I based my own thesis can be found here: >> http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0161788. >> >> My project can be found here: https://github.com/RainVagel/c >> ross-val-cross-test. >> >> Our original plan was to try and get the algorithm into scikit-learn, but >> it doesn’t meet the requirements yet. So instead we thought about maybe >> having it listed in the “Related Projects” page. Is it possible for >> somebody to take a look and give any feedback? >> >> Sincerely, >> Rain >> >> >> >> >> _______________________________________________ >> scikit-learn mailing list >> scikit-learn@python.org >> https://mail.python.org/mailman/listinfo/scikit-learn >> >> >
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