小编DSo*_*thy的帖子

我首先使用以下代码创建了一个线图：

plot = sns.lineplot(data=tips,
             x="sex",
             y="tip",
             ci=50,
             hue="day",
             palette="Accent")
plot.set_title("Value of Tips Given to Waiters, by Days of the Week and Sex", fontsize=24, pad=30, fontdict={"weight": "bold"})
plot.legend("")

我意识到它实际上是我需要的猫图，因此我将代码修改为以下内容：

plot = sns.catplot (data=tips,
             x="day",
             y="tip",
             kind='bar',
             ci=50,
             hue="sex",
             palette="Accent")
plot.set_title("Value of Tips Given to Waiters, by Days of the Week and Sex", fontsize=24, pad=30, fontdict={"weight": "bold"})
plot.legend("")

但是，我收到以下标题错误消息：'AttributeError:'FacetGrid' object has no attribute 'set_title''。

为什么我的标题不适用于猫图？

以下代码使用随机森林模型为我提供一个显示特征重要性的图表：

from sklearn.feature_selection import SelectFromModel
import matplotlib

clf = RandomForestClassifier()
clf = clf.fit(X_train,y_train)
clf.feature_importances_  
model = SelectFromModel(clf, prefit=True)
test_X_new = model.transform(X_test)

matplotlib.rc('figure', figsize=[5,5])
plt.style.use('ggplot')

feat_importances = pd.Series(clf.feature_importances_, index=X_test.columns)
feat_importances.nlargest(20).plot(kind='barh',title = 'Feature Importance')

然而，我需要对逻辑回归模型做同样的事情。以下代码会产生错误：

from sklearn.feature_selection import SelectFromModel
import matplotlib

clf = LogisticRegression()
clf = clf.fit(X_train,y_train)
clf.feature_importances_  
model = SelectFromModel(clf, prefit=True)
test_X_new = model.transform(X_test)

matplotlib.rc('figure', figsize=[5,5])
plt.style.use('ggplot')

feat_importances = pd.Series(clf.feature_importances_, index=X_test.columns)
feat_importances.nlargest(20).plot(kind='barh',title = 'Feature Importance')

我明白了

AttributeError: 'LogisticRegression' object has no attribute 'feature_importances_'

有人可以帮助我哪里出错了吗？