AttributeError: 'GridSearchCV' object has no attribute 'cv_results_'

Question

I try to apply this code :

pipe = make_pipeline(TfidfVectorizer(min_df=5), LogisticRegression())
param_grid = {'logisticregression__C': [ 0.001, 0.01, 0.1, 1, 10, 100],
              "tfidfvectorizer__ngram_range": [(1, 1),(1, 2),(1, 3)]} 

grid = GridSearchCV(pipe, param_grid, cv=5)
grid.fit(text_train, Y_train)

scores = grid.cv_results_['mean_test_score'].reshape(-1, 3).T
# visualize heat map
heatmap = mglearn.tools.heatmap(
scores, xlabel="C", ylabel="ngram_range", cmap="viridis", fmt="%.3f",
xticklabels=param_grid['logisticregression__C'],
yticklabels=param_grid['tfidfvectorizer__ngram_range'])
plt.colorbar(heatmap)

But I have this error :

AttributeError: 'GridSearchCV' object has no attribute 'cv_results_'

Answer 1

Update your scikit-learn, cv_results_ has been introduced in 0.18.1, earlier it was called grid_scores_ and had slightly different structure http://scikit-learn.org/0.17/modules/generated/sklearn.grid_search.GridSearchCV.html#sklearn.grid_search.GridSearchCV

Answer 2

from sklearn.model_selection import GridSearchCV

use this clf.cv_results_

Answer 3

Solved ! Uninstall and install conda scikit learn in 0.18.1 How to upgrade scikit-learn package in anaconda.

When I import GridSearch :

from sklearn.model_selection import GridSearchCV