基于Python贝叶斯的机器学习的可以对输入错误拼写的英文进行模糊查询，输出正确的拼写方式+详细部署文档+全部数据资料 高分项目

import re import collections def words(text): return re.findall('[a-z]+', text.lower()) def train(features): model = collections.defaultdict(lambda: 1) for f in features: model[f] += 1 return model with open(r'C:\Python34\big.txt') as fp: NWORDS = train(words(fp.read())) alphabet = 'abcdefghijklmnopqrstuvwxyz' def edits1(word): splits = [(word[:i], word[i:]) for i in range(len(word) + 1)] deletes = [a + b[1:] for a, b in splits if b] transposes = [a + b[1] + b[0] + b[2:] for a, b in splits if len(b)>1] replaces = [a + c + b[1:] for a, b in splits for c in alphabet if b] inserts = [a + c + b for a, b in splits for c in alphabet] return set(deletes + transposes + replaces + inserts) def known_edits2(word): return set(e2 for e1 in edits1(word) for e2 in edits1(e1) if e2 in NWORDS) def known(words): return set(w for w in words if w in NWORDS) def correct(word): candidates = known([word]) or known(edits1(word)) or known_edits2(word) or [word] return max(candidates, key=NWORDS.get)