8.6.2 决策树算法原理与Sklearn 实现

import numpy as np
from sklearn import tree
X = np.array([[0,0,0],[0,0,1],[0,1,0],[0,1,1],[1,0,0],[1,0,1],[1,1,0],[1,1,1]])
y = [0,1,1,1,2,3,3,4]
clf = tree.DecisionTreeClassifier()
clf.fit(X,y)

clf.predict([[1,0,0]])

import graphviz
dot_data = tree.export_graphviz(clf, out_file=None)
graph = graphviz.Source(dot_data)
graph.render('result')

result.pdf