如何使用Python中的决策树进行聚类的可视化

import numpy as np
import pandas as pd
from sklearn.datasets import make_classification
from sklearn.model_selection import train_test_split
from sklearn.tree import DecisionTreeClassifier, export_graphviz
from sklearn import tree

X, y = make_classification(n_samples=1000, n_features=4,
                            n_informative=2, n_redundant=0,
                            random_state=0, shuffle=False)

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0)

clf = DecisionTreeClassifier(max_depth=3)
clf.fit(X_train, y_train)

export_graphviz(clf, out_file='tree.dot',
               feature_names=['pidancode', 'com', 'size', 'age'],
               class_names=['0', '1'],
               filled=True, rounded=True,
               special_characters=True)

!dot -Tpng tree.dot -o tree.png

from IPython.display import Image
Image(filename='tree.png')