taken from siraj raval's python for data science video #1

predictGender.py

# decision tree that creates branches for every possible outcome
from sklearn import tree

# list of lists -- each value is the length, width and shoe size
X = [[181,80,44],[177,70,43],[160,60,38],
     [154,54,37],[166,65,40],[190,90,47],
     [175,64,39],[177,70,40],[159,55,37],
     [171,75,42],[181,85,43]]

Y = ['male', 'female', 'female', 'female', 'male', 'male',
      'male', 'female', 'male', 'female', 'male']

clf = tree.DecisionTreeClassifier()

clf = clf.fit(X,Y)

prediction = clf.predict([[190,70,43]])

print(prediction)