在没有统计元数据的情况下呈现一个scikit learn DecisionTreeClassifier？

from sklearn.datasets import load_iris
from sklearn.tree import DecisionTreeClassifier
from sklearn import tree
import matplotlib.pyplot as plt

iris = load_iris()
X = iris.data
y = iris.target

clf = DecisionTreeClassifier()
clf.fit(X, y)

fig = plt.figure(figsize=(10, 8))
_ = tree.plot_tree(clf, 
                   feature_names=iris.feature_names,  
                   class_names=iris.target_names)
plt.show()