Python 決策樹 生成PDF
阿新 • • 發佈:2019-02-20
包準備pydot、graphviz安裝conda install graphviz(完整安裝)pip install pydot 降級安裝示例 pip install robotframework==2.8.7 #生成決策樹
from sklearn.datasets import load_iris
from sklearn import tree
iris = load_iris()
clf = tree.DecisionTreeClassifier()
clf = clf.fit(iris.data, iris.target)
results=clf.predict_proba(iris.data)#生成PDFfrom sklearn.externals.six import StringIO
with open("iris.dot", 'w') as f:
f = tree.export_graphviz(clf, out_file=f)
os.unlink('iris.dot')
from sklearn.externals.six import StringIO
import pydotplus
dot_data = StringIO()
tree.export_graphviz(clf, out_file=dot_data)
graph = pydotplus.graph_from_dot_data(dot_data.getvalue())
graph.write_pdf("iris.pdf")
from IPython.display import Image
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,
special_characters=True)
graph = pydotplus.graph_from_dot_data(dot_data.getvalue())
Image(graph.create_png())
import pandas as pd
from sklearn.datasets import load_iris
from sklearn import tree
iris = load_iris()
clf = tree.DecisionTreeClassifier()
clf = clf.fit(iris.data, iris.target)
results=clf.predict_proba(iris.data)#生成PDFfrom sklearn.externals.six import StringIO
with open("iris.dot", 'w') as f:
f = tree.export_graphviz(clf, out_file=f)
os.unlink('iris.dot')
from sklearn.externals.six import StringIO
import pydotplus
dot_data = StringIO()
tree.export_graphviz(clf, out_file=dot_data)
graph = pydotplus.graph_from_dot_data(dot_data.getvalue())
graph.write_pdf("iris.pdf")
from IPython.display import Image
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,
special_characters=True)
graph = pydotplus.graph_from_dot_data(dot_data.getvalue())
Image(graph.create_png())