Hi Paul.
Doing the documentation is in the issue tracker, but no-one wrote it yet :-/
The unpickled model should be trained, i.e. it is not necessary to
re-run fit.
Running fit again will just forget the old model.
Hth,
Andy
On 01/04/2013 05:19 PM, [email protected] wrote:
Dear SciKitters,
there is one thing I don't understand when cPickling a model. Here is
my code to pickle a model:
"
clf_kNN = KNeighborsClassifier()
clf_kNN = clf_kNN.fit(dataDescrs_array,dataActs_array)
cPickle.dump(clf_kNN,file("clf_kNN.descr.pk","wb+"))
"
And this is the way to extract the model:
"
kNN_clf_frompkl = cPickle.load(file("./clf_kNN.descr.pkl","rb"))
y_predict = kNN_clf_frompkl.predict(X_test)
#
kNN_clf_frompkl = kNN_clf_frompkl.fit(X_train,y_train)
y_predict2 = kNN_clf_frompkl.predict(X_test)
"
Is it necessary to run the "fit" step? - in my understanding,
"kNN_clf_frompkl" already contains a kNN model.
What is the difference between the loaded models with and without the
"fit" step?
Is there any documentation about cPickling models? The only
documentation I found comes from the mailing list.
Cheers & Thanks,
Paul
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