Yeah, right. I didn't think about that. I'll check in the source how the data
is stored.
Thanks for helping sort it all out.
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I am using the nltk.classify.MaxEntClassifier. This object has a set of labels,
and a set of probabilities: P(label | features). It modifies this probability
given data. SO for example, if you tell this object that the label L appears
60% of the time with the feature F, then P(L | F) = 0.6.
The
I see. In that case, all I have to do is make sure NLTK is available when I
load the pickled objects. That pretty much solves my problem. Thanks!
So it means pickle doesn't ever save the object's values, only how it was
created?
Say I have a large object that requires a lot of time to train on
You're probably right in general, for me the 3.3 and 2.7 pickles definitely
don't work the same:
3.3:
>>> type(pickle.dumps(1))
2.7:
>>> type(pickle.dumps(1, pickle.HIGHEST_PROTOCOL))
As you can see, in 2.7 when I try to dump something, I get useless string. Look
what I gen when I dump an N
Hi all,
I'm working on a project in Python 2.7. I have a few large objects, and I want
to save them for later use, so that it will be possible to load them whole from
a file, instead of creating them every time anew. It is critical that they be
transportable between platforms. Problem is, when
