2014/1/10 Robert Layton <robertlay...@gmail.com>: > I wonder if that check could be removed -- as long as the input is > fancy-indexable, the code should otherwise not have an issue (until it hits > the distance metric, in which case you have that covered).
-1. Since high-d data is usually a mistake and NumPy offers easy reshaping for the advanced use cases, I think we should leave the code as is. It fits the existing convention that an array has shape (n_samples, n_features) and raises a very clear exception. Passing higher-d data on would raise an exception deep down in the k-NN code, making debugging of easy mistakes harder. ------------------------------------------------------------------------------ CenturyLink Cloud: The Leader in Enterprise Cloud Services. Learn Why More Businesses Are Choosing CenturyLink Cloud For Critical Workloads, Development Environments & Everything In Between. Get a Quote or Start a Free Trial Today. http://pubads.g.doubleclick.net/gampad/clk?id=119420431&iu=/4140/ostg.clktrk _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
