Hi Anton, The update for each sample is just multiplied by the sample_weight and the class_weight before it's applied to the weight vector (coef_). So if your sample is [1, 2, 3], your gradient is .1, your weight for this sample is .2, and your eta is 5.0 your weight_vector (coef_) would be updated by [+(1 * .1 * .2 * 5.0), +(2 * .1 * .2 * 5.0), +(3 *.1 * .2 * 5.0)]. Does that help?
Danny On Thu, Jun 25, 2015 at 10:19 AM, Anton Suchaneck <a.suchan...@gmail.com> wrote: > Hello! > > How can I find out what the precise mathematical treatment of the > sample_weights for SGDClassifier in the partial_fit setting is? > > Cheers, > Anton > > > ------------------------------------------------------------------------------ > Monitor 25 network devices or servers for free with OpManager! > OpManager is web-based network management software that monitors > network devices and physical & virtual servers, alerts via email & sms > for fault. Monitor 25 devices for free with no restriction. Download now > http://ad.doubleclick.net/ddm/clk/292181274;119417398;o > _______________________________________________ > Scikit-learn-general mailing list > Scikit-learn-general@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > ------------------------------------------------------------------------------ Monitor 25 network devices or servers for free with OpManager! OpManager is web-based network management software that monitors network devices and physical & virtual servers, alerts via email & sms for fault. Monitor 25 devices for free with no restriction. Download now http://ad.doubleclick.net/ddm/clk/292181274;119417398;o _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
