【发布时间】:2017-05-22 07:54:49
【问题描述】:
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_'
【问题讨论】:
-
你用的是什么版本的python/sklearn?
-
Python 的版本 3.5.2 但是当我检查 sklearn 版本时:0.0.当我更新 scikit-learn 时,Sklearn 会自动更新?
标签: python machine-learning scikit-learn text-mining