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It's awkward to actually get an instance of the best fitted model. Right now I've got to do:
from scipy import stats
((name, params),) = fitter.get_best().items()
model = getattr(stats, name)(**params)
I think it would make more sense if the get_best actually returned the fitted model and some other method gave you the parameters. Look at the sklearn GridSearch where after calling fit, the fitter behaves as the best fitted model, and one can extract the best model and best params easily. https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.GridSearchCV.html
The text was updated successfully, but these errors were encountered:
It's awkward to actually get an instance of the best fitted model. Right now I've got to do:
I think it would make more sense if the get_best actually returned the fitted model and some other method gave you the parameters. Look at the sklearn GridSearch where after calling fit, the fitter behaves as the best fitted model, and one can extract the best model and best params easily. https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.GridSearchCV.html
The text was updated successfully, but these errors were encountered: