《机器学习(周志华)》笔记--决策树（6）--决策树构造代码实现

八、决策树构造

from sklearn import tree
#决策树生成
clf = tree.DecisionTreeClassifier(criterion='entropy')
clf = tree.DecisionTreeClassifier(criterion='gini')
clf.fit(X,Y)
dot_data = StringIO()
tree.export_graphviz(clf, out_file = dot_data, feature_names=['color','root','sound','texture','navel','feeling'], class_names=['good','bad']) #决策树可视化
graph = pydotplus.graph_from_dot_data(dot_data.getvalue())
graph.write_pdf("tree.pdf")
                    

具体代码实现：

import pandas as pd
from sklearn import tree
import pydotplus
from sklearn.externals.six import StringIO

df = pd.read_csv('ex4.csv',header=None)
data = df.values
X=data[:,:-1]
Y=data[:,-1]
clf = tree.DecisionTreeClassifier(criterion='entropy')
clf.fit(X,Y)
dot_data = StringIO()
tree.export_graphviz(clf, out_file = dot_data,\
                    feature_names=['color','root','sound','texture','navel','feeling'],\
                    class_names=['good','bad'])
graph = pydotplus.graph_from_dot_data(dot_data.getvalue())
graph.write_pdf("tree.pdf")