我正在积极学习如何在python中实现决策树.

当从scikit-learn重新创建Iris分类示例时,我得到了export_graphviz中存在的参数的TypeError,即’class_names’和’plot_options’.

from IPython.display import Image  
import sklearn
dot_data = StringIO()  
sklearn.tree.export_graphviz(clf, out_file=dot_data,
                     plot_options=['class', 'filled', 'label', 'sample',       'proportion'],
                 target_names=iris['target_names'],
                 feature_names=iris['feature_names'])
graph = pydot.graph_from_dot_data(dot_data.getvalue())  
Image(graph.create_png()) 

上面特定代码的错误是：

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-33-aba117838252> in <module>()
      5                      plot_options=['class', 'filled', 'label', 'sample', 'proportion'],
      6                      target_names=iris['target_names'],
----> 7                      feature_names=iris['feature_names'])
      8 graph = pydot.graph_from_dot_data(dot_data.getvalue())
      9 Image(graph.create_png())

TypeError: export_graphviz() got an unexpected keyword argument 'plot_options'

在我的电脑上,我安装了graphviz和pydot2.
我在尝试安装pygraphviz时收到错误：

 If you think your installation is correct you will need to manually

    change the include_dirs and library_dirs variables in setup.py to

    point to the correct locations of your graphviz installation.



    The current setting of library_dirs and include_dirs is:

library_dirs=None

include_dirs=None

error: Error locating graphviz.

是否有解决方案允许我使用export_graphviz中的参数来构建我想要的树形象化？
寻求pygraphviz安装错误的解决方案导致我的树的解决方案？

谢谢,

解决方法:

export_graphviz的签名是

def export_graphviz(decision_tree, out_file="tree.dot", max_depth=None,
                feature_names=None, class_names=None, label='all',
                filled=False, leaves_parallel=False, impurity=True,
                node_ids=False, proportion=False, rotate=False,
                rounded=False, special_characters=False):

正确的函数调用是(假设您的数据在iris对象中)

sklearn.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) 

如果它抛出错误

TypeError：export_graphviz()得到一个意外的关键字参数’class_names’

这意味着你的sklearn是旧版本.如果您使用的是anaconda python发行版,则可以使用更新到最新版本的sklearn
conda更新scikit-learn.如果您在任何其他发行版上,请使用pip命令.确保您的sklearn是0.17版本.

import sklearn
print sklearn.__version__