In [1]:

    

import sklearn


    

In [2]:

    

features = [[100,"smooth"],[200,"bumpy"],[120,"smooth"],[220,"bumpy"],[110,"smooth"],[240,"bumpy"]]


    

In [3]:

    

labels = ["apple","orange","apple","orange","apple","orange"]


    

In [4]:

    

#smooth=0, apple=0
#bumpy=1,orange=1
features = [[100,0],[200,1],[120,0],[220,1],[110,0],[240,1]]
labels = [0,1,0,1,0,1]


    

In [6]:

    

from sklearn import tree
clf = tree.DecisionTreeClassifier()


    

In [7]:

    

clf = clf.fit(features,labels)


    

In [9]:

    

print clf.predict([[160,0]])


    

    




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