本文演示使用NLTK让计算机学习如何通过名字识别性别。
1、导入NLTK：
import nltk
from nltk.book import *
2、定义学习方法
def gender_features(word):
return {'last_letter':word[-1]}
3、导入学习的姓名-性别名单：
from nltk.corpus import names
import random
names=([(name,'male') for name in names.words('male.txt')] + [(name,'female') for name in names.words('female.txt')])
random.shuffle(names)
4、开始学习
f = [(gender_features(n),g) for (n,g) in names]
trainset,testset = f[500:],f[:500]
c = nltk.NaiveBayesClassifier.train(trainset)
5、测试：
c.classify(gender_features('Neo'))
c.classify(gender_features('Trinity'))
