Hi all, I just started using sklearn nearest-neighbors for classification & would like to apply my own distance weighting function.
To do this I need to know exactly what the 'distance' that is fed to the function represents. (Current documentation doesn't give me an immediate answer.) For example if I set p=2 do I get the Euclidean distance, i.e. the square root of the sums of squares of coordinate differences; or the square of it? If p>2 do I get the distance, in the sense of the p-th root of sum of p-th powers, or the p-th power of distance? Thanks, Tom -- ----------------------------------------- Institute for Gravitational Physics (Albert Einstein Institute) Callinstr. 38 D-30167 Hannover, Germany ------------------------------------------------------------------------------ Master Visual Studio, SharePoint, SQL, ASP.NET, C# 2012, HTML5, CSS, MVC, Windows 8 Apps, JavaScript and much more. Keep your skills current with LearnDevNow - 3,200 step-by-step video tutorials by Microsoft MVPs and experts. SALE $99.99 this month only -- learn more at: http://p.sf.net/sfu/learnmore_122412 _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
