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

Question

我尝试应用此代码：

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)

但是我有这个错误:

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

Answer 1

更新您的 scikit-learn，cv_results_ 已在 0.18.1 中引入，之前称为 grid_scores_ 并且结构略有不同 http://scikit-learn.org/0.17/modules/generated/sklearn.grid_search.GridSearchCV.html#sklearn.grid_search.GridSearchCV

Answer 2

已解决！在 0.18.1 How to upgrade scikit-learn package in anaconda.

中卸载并安装 conda scikit learn

当我导入 GridSearch 时：

from sklearn.model_selection import GridSearchCV

Answer 3

首先，您应该更新您的 scklearn，使用：

pip install -U scikit-learn

之后，检查你是否包含了错误的模块：

from sklearn.grid_search import GridSearchCV

更改为新路径：

from sklearn.model_selection import GridSearchCV

（这是正确的方法）

Answer 4

从 sklearn.model_selection 导入 GridSearchCV

使用这个clf.cv_results_

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

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

python

machine-learning

text-mining

scikit-learn