Thanks to Andreas I got it working now using a custom estimator for the pipeline.
I am still struggling a bit to combine textual features (e.g., tfidf) with other features that work well on their own. At the moment, I am just concatanating them --> enlarging the vector. The problem now is, that the few added features do not seem to have any impact on the classifier, as the accuracy is exactly the same as if I would use only textual features. They just seem to be overwhelmed by the huge amount of textual features. Is there now some clever way of combining both feature types? Like probably using composite/multiple kernels? Maybe someone has an idea about that. This is actually a thing, I am struggling for a bit now and still haven't found a clever way of solving it. Regards, Philipp ------------------------------------------------------------------------------ LogMeIn Rescue: Anywhere, Anytime Remote support for IT. Free Trial Remotely access PCs and mobile devices and provide instant support Improve your efficiency, and focus on delivering more value-add services Discover what IT Professionals Know. Rescue delivers http://p.sf.net/sfu/logmein_12329d2d _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
