1. use sklearn to predict
from sklearn import tree
features = [[140,1],[130,1],[150,0],[170,0]]
labels = [0,0,1,1]
clf = tree.DecisionTreeClassifier()
clf = clf.fit(features, labels)
print clf.predict([[150,0]])
from sklearn import tree
features = [[140,1],[130,1],[150,0],[170,0]]
labels = [0,0,1,1]
clf = tree.DecisionTreeClassifier()
clf = clf.fit(features, labels)
print clf.predict([[150,0]])