乔守卿*_*乔守卿 45 python machine-learning graphviz pydot scikit-learn
我的代码是遵循谷歌的机器学习类.两个代码是相同的.我不知道为什么它显示错误.可能是变量的类型是错误.但谷歌的代码对我来说是相同的.谁有过这个问题?
这是错误的
[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]
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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")
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ave*_*ble 66
我想你正在使用更新版本的python.请尝试使用pydotplus.
import pydotplus
...
graph = pydotplus.graph_from_dot_data(dot_data.getvalue())
graph.write_pdf("iris.pdf")
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这应该做到这一点.
Ili*_*bev 25
pydot.graph_from_dot_data() 返回一个列表,所以尝试:
graph = pydot.graph_from_dot_data(dot_data.getvalue())
graph[0].write_pdf("iris.pdf")
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