2012/1/9 Mathias Verbeke <[email protected]>: > Dear all, > > In the documentation of the SVM module, I saw that it was possible to pass > your own Gram matrix to the kernel. I was wondering if it was also possible > to do the reverse, i.e. to export the calculated Gram matrix (that gives the > similarity between the train and test instances)?
libsvm computes the kernel matrix lazily and throws away the rows it no longer need during the computation (configurable using the cache_size parameters). If you want to compute explicit kernel matrices have a look at: http://scikit-learn.org/dev/modules/classes.html#module-sklearn.metrics.pairwise And in particular: http://scikit-learn.org/dev/modules/generated/sklearn.metrics.pairwise.kernel_metrics.html#sklearn.metrics.pairwise.kernel_metrics -- Olivier http://twitter.com/ogrisel - http://github.com/ogrisel ------------------------------------------------------------------------------ Ridiculously easy VDI. With Citrix VDI-in-a-Box, you don't need a complex infrastructure or vast IT resources to deliver seamless, secure access to virtual desktops. With this all-in-one solution, easily deploy virtual desktops for less than the cost of PCs and save 60% on VDI infrastructure costs. Try it free! http://p.sf.net/sfu/Citrix-VDIinabox _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
