AttributeError：'GridSearchCV'对象没有属性'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_，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

解决了！ 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

从sklearn.model_selection导入GridSearchCV

使用此clf.cv_results_

Answer 4

首先，你应该使用：

更新你的scklearn

pip install -U scikit-learn

之后，检查您是否包含错误的模块：

from sklearn.grid_search import GridSearchCV

更改为新路径：

from sklearn.model_selection import GridSearchCV

（这是正确的方式）