求求各位大神了！
from sklearn import datasets
from sklearn import tree
from sklearn.externals.six import StringIO
import pydot
import numpy as np
iris = datasets.load_iris() # 加載Iris資料集
# 載入特征和標簽集
x = [[1, 1], [1, 1], [1, 0], [0, 1], [0, 1]]
x=np.array(x)
y = ['1', '1', '0', '0', '0']
y=np.array(y)
z = ['浮出水面', '有無腳蹼']
p = ['是魚類', '否魚類']
p=np.array(p)
clf = tree.DecisionTreeClassifier() # 構建決策樹，默認是gini指標
#clf = clf.fit(iris.data, iris.target)
clf = tree.DecisionTreeClassifier()
clf = clf.fit(x, y)
dot_data = StringIO()
tree.export_graphviz(clf, out_file=dot_data, feature_names=z, class_names=p, filled=True, rounded=True, special_characters=True)
#tree.export_graphviz(clf, out_file=dot_data, feature_names=iris.feature_names, class_names=iris.target_names, filled=True, rounded=True, special_characters=True)
#tree.export_graphviz(clf, out_file=r"tree.dot") #把這行代碼放開可以生成決策樹的檔案
(graph,) = pydot.graph_from_dot_data(dot_data.getvalue())
graph.write_png('iris.png')
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