I'm trying to use recursive feature elimination with gradient boosting and grid
search as shown below
gbr = GradientBoostingClassifier()
parameters = {'learning_rate': [0.1, 0.01, 0.001],
'max_depth': [1, 4, 6],
'min_samples_leaf': [3, 5, 9, 17],
'max_features': [1.0, 0.3, 0.1]}
clf = grid_search.GridSearchCV(estimator=gbr, param_grid=parameters,
n_jobs=16)
rfecv = RFECV(estimator=clf, step=1, cv=10, scoring='accuracy')
rfecv.fit(x_train, y_train)
# prediction
y_predicted = rfecv.estimator_.predict(x_test)
However, I'm getting this error and I don't know how to fix it:
Traceback (most recent call last):
File "./gbr_rfe.py", line 92, in <module>
rfecv.fit(x_train, y_train)
File
"/usr/local/lib/python2.7/dist-packages/sklearn/feature_selection/rfe.py", line
376, in fit
ranking_ = rfe.fit(X_train, y_train).ranking_
File
"/usr/local/lib/python2.7/dist-packages/sklearn/feature_selection/rfe.py", line
163, in fit
if estimator.coef_.ndim > 1:
AttributeError: 'GridSearchCV' object has no attribute 'coef_'
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