great package! I really like the simplicity and the speed improvement.
I have users that would like to be able to use both "versions" of the classifier and I would like to find an easy way to differentiate between the two directly after loading them.
so far I came up with based on it's object description:
with open(path_to_sav,"rb") as f:
clf= pickle.load(f)
if 'pure' in str(clf):
print(clf)
Output:
<pure_sklearn.ensemble._forest.RandomForestClassifierPure object at 0x00000201490EEF98>
Hi,
great package! I really like the simplicity and the speed improvement.
I have users that would like to be able to use both "versions" of the classifier and I would like to find an easy way to differentiate between the two directly after loading them.
so far I came up with based on it's object description:
Is there a better way to do this?