#!dt/bin/python3
 from sklearn import tree
 import pydotplus

 X=[[0,0],\
    [0,1],\
    [1,0],\
    [1,1]]

 Y=[0,0,0,1]

 clf = tree.DecisionTreeClassifier()
 clf = clf.fit(X, Y)

   # dump decision tree
 dot_data = tree.export_graphviz(
     clf, out_file=None,
     filled=True, rounded=True,
     feature_names=['X','Y'],
     class_names=['0','1'])
 graph = \
     pydotplus.graph_from_dot_data(dot_data)
 graph.write_png("tree.png")

   # Check predictions
 for input in X:
     print( input, ":",
            clf.predict( [input] ) )