Re: [Rdkit-discuss] cmp -> store model on disk

2011-08-21 Thread Paul . Czodrowski
Dear Greg,


> Dear Paul,
>
> On Sat, Aug 20, 2011 at 4:35 PM,  wrote:
> >
> > after having trained a model
> > "
> > cmp = Composite()
> > cmp.Grow
> > (pts,attrs=attrs,nPossibleVals=nPossible,nTries=1,
>
buildDriver=CrossValidate.CrossValidationDriver,treeBuilder=QuantTreeBoot,
> >  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

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Re: [Rdkit-discuss] cmp -> store model on disk

2011-08-21 Thread Greg Landrum
Dear Paul,

On Sat, Aug 20, 2011 at 4:35 PM,  wrote:
>
> after having trained a model
> "
> cmp = Composite()
> cmp.Grow
> (pts,attrs=attrs,nPossibleVals=nPossible,nTries=1,buildDriver=CrossValidate.CrossValidationDriver,treeBuilder=QuantTreeBoot,
>  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+'))

> 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

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[Rdkit-discuss] cmp -> store model on disk

2011-08-20 Thread Paul . Czodrowski

Dear RDkitters,

after having trained a model
"
cmp = Composite()
cmp.Grow
(pts,attrs=attrs,nPossibleVals=nPossible,nTries=1,buildDriver=CrossValidate.CrossValidationDriver,treeBuilder=QuantTreeBoot,
 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?

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?

Cheers & Thanks,
Paul

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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.


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