2014-07-08 16:00 GMT+02:00 Michael Eickenberg <michael.eickenb...@gmail.com>: > That totally depends on your data. Here it looks like you are scaling down a > feature that captures a lot of the variation you are looking for, thus > making it less important with respect to the other features in the euclidean > distance. You could try selecting important features beforehand. But they > may be non-coordinate directions in your feature space as well.
It also depends on whether you did the scaling right. How did you scale the test set? ------------------------------------------------------------------------------ Open source business process management suite built on Java and Eclipse Turn processes into business applications with Bonita BPM Community Edition Quickly connect people, data, and systems into organized workflows Winner of BOSSIE, CODIE, OW2 and Gartner awards http://p.sf.net/sfu/Bonitasoft _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
