graph.write_pdf("iris.pdf")AttributeError:“列表"对象没有属性"write_pdf" [英] graph.write_pdf("iris.pdf") AttributeError: 'list' object has no attribute 'write_pdf'

问题描述

我的代码遵循google的机器学习课程.两个代码是相同的.我不知道为什么会显示错误.可能是变量的类型是错误.但是google的代码对我来说是相同的.曾经遇到过这个问题吗?

My code is follow the class of machine learning of google.The two code are same.I don't know why it show error.May be the type of variable is error.But google's code is same to me.Who has ever had this problem?

这是错误

[0 1 2]
[0 1 2]
Traceback (most recent call last):
  File "/media/joyce/oreo/python/machine_learn/VisualizingADecisionTree.py", line 34, in <module>
    graph.write_pdf("iris.pdf")
AttributeError: 'list' object has no attribute 'write_pdf'
[Finished in 0.4s with exit code 1]
[shell_cmd: python -u "/media/joyce/oreo/python/machine_learn/VisualizingADecisionTree.py"]
[dir: /media/joyce/oreo/python/machine_learn]
[path: /usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games]

这是代码

import numpy as np
from sklearn.datasets import load_iris
from sklearn import tree

iris = load_iris()
test_idx = [0, 50, 100]

# training data
train_target = np.delete(iris.target, test_idx)
train_data = np.delete(iris.data, test_idx, axis=0)

# testing data
test_target = iris.target[test_idx]
test_data = iris.data[test_idx]

clf = tree.DecisionTreeClassifier()
clf.fit(train_data, train_target)

print test_target
print clf.predict(test_data) 

# viz code
from sklearn.externals.six import StringIO
import pydot
dot_data = StringIO()
tree.export_graphviz(clf,
        out_file=dot_data,
        feature_names=iris.feature_names,
        class_names=iris.target_names,
        filled=True, rounded=True,
        impurity=False)

graph = pydot.graph_from_dot_data(dot_data.getvalue())
graph.write_pdf("iris.pdf")

推荐答案

pydot.graph_from_dot_data()返回列表，因此请尝试:

pydot.graph_from_dot_data() returns a list, so try:

graph = pydot.graph_from_dot_data(dot_data.getvalue())
graph[0].write_pdf("iris.pdf") 

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