Thanks for pointing it out! (And I'll check things out a little more carefully in the future before posting.)
On Sat, May 18, 2013 at 8:22 AM, Lars Buitinck <[email protected]> wrote: > 2013/5/18 James Bergstra <[email protected]>: >> Is there a convention / plan for how example weights should be passed to >> fit? An optional keyword argument? A new fit_weighted method that may or may >> not be present? How would this work together with the incremental fit >> mechanism? > > A sample_weight argument to fit. I believe most of the linear models > already do this, check that module. > >> I ask because we were talking about boosting algorithms the other day, and >> it's natural to implement boosting in terms of reweighted training examples. > > This is in fact how AdaBoost is implemented in sklearn.ensemble. > > -- > Lars Buitinck > Scientific programmer, ILPS > University of Amsterdam > > ------------------------------------------------------------------------------ > AlienVault Unified Security Management (USM) platform delivers complete > security visibility with the essential security capabilities. Easily and > efficiently configure, manage, and operate all of your security controls > from a single console and one unified framework. Download a free trial. > http://p.sf.net/sfu/alienvault_d2d > _______________________________________________ > Scikit-learn-general mailing list > [email protected] > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general ------------------------------------------------------------------------------ Try New Relic Now & We'll Send You this Cool Shirt New Relic is the only SaaS-based application performance monitoring service that delivers powerful full stack analytics. Optimize and monitor your browser, app, & servers with just a few lines of code. Try New Relic and get this awesome Nerd Life shirt! http://p.sf.net/sfu/newrelic_d2d_may _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
