Cox*_*Tox 6 python machine-learning text-mining scikit-learn
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)
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但我有这个错误:
AttributeError: 'GridSearchCV' object has no attribute 'cv_results_'
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lej*_*lot 14
更新你的scikit-learn,cv_results_
已在0.18.1中引入,之前它被调用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
从 sklearn.model_selection 导入 GridSearchCV
用这个 clf.cv_results_
解决了 !在 0.18.1如何在 anaconda 中升级 scikit-learn 包中卸载并安装conda scikit learn。
当我导入 GridSearch 时:
from sklearn.model_selection import GridSearchCV
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