in the documentation says boruta implements all scikit-learn ensemble methods, but it doesn't work with HistGradientBoostingClassifier. Other methods described on the ensemble documentation (such as adaboost and gradient tree boosting) work as expected.
Thanks
Reprex
from boruta import BorutaPy
from sklearn.experimental import enable_hist_gradient_boosting
from sklearn.ensemble import HistGradientBoostingClassifier
clf = HistGradientBoostingClassifier()
boruta = BorutaPy(
estimator=clf,
n_estimators='auto',
max_iter=10)
boruta.fit(np.array(X_train), np.array(y_train))
Error message
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
in
---> 18 boruta.fit(np.array(X_train), np.array(y_train))
~/.pyenv/versions/python-3.7.4/lib/python3.7/site-packages/boruta/boruta_py.py in fit(self, X, y)
199 """
200
--> 201 return self._fit(X, y)
202
203 def transform(self, X, weak=False):
~/.pyenv/versions/python-3.7.4/lib/python3.7/site-packages/boruta/boruta_py.py in _fit(self, X, y)
268 # set n_estimators
269 if self.n_estimators != 'auto':
--> 270 self.estimator.set_params(n_estimators=self.n_estimators)
271
272 # main feature selection loop
~/.pyenv/versions/python-3.7.4/lib/python3.7/site-packages/sklearn/base.py in set_params(self, **params)
250 'Check the list of available parameters '
251 'with `estimator.get_params().keys()`.' %
--> 252 (key, self))
253
254 if delim:
ValueError: Invalid parameter n_estimators for estimator HistGradientBoostingClassifier(). Check the list of available parameters with `estimator.get_params().keys()`.
Hi 👋
in the documentation says
boruta
implements all scikit-learn ensemble methods, but it doesn't work withHistGradientBoostingClassifier
. Other methods described on the ensemble documentation (such asadaboost
andgradient tree boosting
) work as expected.Thanks
Reprex
Error message