Here is a comparison to output of my code (marked with >): 0.00458652660079 0.788017364828 0.00700027844478 0.00483928213727 > 0.145564526722 0.480124905375 0.422482399359 0.217567496918 6.50616752373e-07 7.99461373461e-05 0.00700027844478 0.0094610687282 > 0.120884106118 0.249205123601 0.422482399359 0.556949542822 0.00760091429285 0.819325410184 0.00909659010031 0.0094610687282 > 0.108943679969 0.195731527474 0.556245690994 0.556949542822 9.30536435524e-08 9.96844926893e-06 0.00921024880111 0.0094610687282 > 0.0362155612112 0.0648617517611 0.559754044038 0.556949542822
;) On Fri, 15 Jun 2012, [email protected] wrote: > >>> here is my attempt: > >>> > >>> [1]https://github.com/satra/scikit-learn/blob/enh/covariance/sklearn/covariance/distance_covariance.py > >>> i'll look at your code in detail later today to understand the uv=True > > trying to see how well this works, here's my gist > > https://gist.github.com/2938402 > (univariate only) > > bretzel and cosine have essentially zero distance correlation ?? -- Yaroslav O. Halchenko Postdoctoral Fellow, Department of Psychological and Brain Sciences Dartmouth College, 419 Moore Hall, Hinman Box 6207, Hanover, NH 03755 Phone: +1 (603) 646-9834 Fax: +1 (603) 646-1419 WWW: http://www.linkedin.com/in/yarik ------------------------------------------------------------------------------ Live Security Virtual Conference Exclusive live event will cover all the ways today's security and threat landscape has changed and how IT managers can respond. Discussions will include endpoint security, mobile security and the latest in malware threats. http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/ _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
