Dear Greg,
> Dear Paul, > > On Sat, Aug 20, 2011 at 4:35 PM, <[email protected]> wrote: > > > > after having trained a model > > " > > cmp = Composite() > > cmp.Grow > > (pts,attrs=attrs,nPossibleVals=nPossible,nTries=1, > buildDriver=CrossValidate.CrossValidationDriver,treeBuilder=QuantTreeBoot, > > Â needsQuantization=False,nQuantBounds=boundsPerVar, maxDepth=3) > > " > > > > How can this model be stored on disk? > > pickle will not help me, because this only works for molecules, or am I > > wrong? > > You should be able to store it to disk by pickling without problems, > something like: > cPickle.dump(cmp,file('cmp.pkl','wb+')) Too easy solution - I would not have dared to just try it... :) > > > I would like to store this model on disk, because I would like predict > > molecules in a later stage without training evry time running the > > prediction. > > For the prediction part, I will be using "cmp.ClassifyExample()" - or is > > there any other possibility? > > Pickling the models and then using ClassifyExample is correct. > > Best, > -greg Thanks, Greg! Paul This message and any attachment are confidential and may be privileged or otherwise protected from disclosure. If you are not the intended recipient, you must not copy this message or attachment or disclose the contents to any other person. If you have received this transmission in error, please notify the sender immediately and delete the message and any attachment from your system. Merck KGaA, Darmstadt, Germany and any of its subsidiaries do not accept liability for any omissions or errors in this message which may arise as a result of E-Mail-transmission or for damages resulting from any unauthorized changes of the content of this message and any attachment thereto. Merck KGaA, Darmstadt, Germany and any of its subsidiaries do not guarantee that this message is free of viruses and does not accept liability for any damages caused by any virus transmitted therewith. Click http://disclaimer.merck.de to access the German, French, Spanish and Portuguese versions of this disclaimer. ------------------------------------------------------------------------------ uberSVN's rich system and user administration capabilities and model configuration take the hassle out of deploying and managing Subversion and the tools developers use with it. Learn more about uberSVN and get a free download at: http://p.sf.net/sfu/wandisco-dev2dev _______________________________________________ Rdkit-discuss mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/rdkit-discuss
