#toy data set
from  sklearn.tree import DecisionTreeClassifier
features=[[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]]
#hws
y=['male','male','female','female','male','male','female','female','female','male','male']

clf=DecisionTreeClassifier()

clf.fit(features,y) #train

p=clf.predict([190,70,43])       #prediction sample
print("prediction=",p)
