敏捷数据科学 - 数据增强

数据增强是指用于增强、改进和优化原始数据的一系列流程。它指有用的数据转换（将原始数据转换为有用的信息）。数据增强流程专注于将数据变成现代业务或企业的宝贵数据资产。

最常见的数据增强流程包括使用特定的决策算法来纠正数据库中的拼写错误或印刷错误。数据增强工具将有用的信息添加到简单的数据库表中。

考虑以下单词拼写纠正代码 -

import re
from collections import Counter
def words(text): return re.findall(r'\w+', text.lower())
WORDS = Counter(words(open('big.txt').read()))

def P(word, N=sum(WORDS.values())):
   "Probabilities of words"
   return WORDS[word] / N
	
def correction(word):
   "Spelling correction of word"
   return max(candidates(word), key=P)
	
def candidates(word):
   "Generate possible spelling corrections for word."
   return (known([word]) or known(edits1(word)) or known(edits2(word)) or [word])
	
def known(words):
   "The subset of `words` that appear in the dictionary of WORDS."
   return set(w for w in words if w in WORDS)
	
def edits1(word):
   "All edits that are one edit away from `word`."
   letters = 'abcdefghijklmnopqrstuvwxyz'
   splits = [(word[:i], word[i:]) for i in range(len(word) + 1)]
   deletes = [L + R[1:] for L, R in splits if R]
   transposes = [L + R[1] + R[0] + R[2:] for L, R in splits if len(R)>1]
   replaces = [L + c + R[1:] for L, R in splits if R for c in letters]
   inserts = [L + c + R for L, R in splits for c in letters]
   return set(deletes + transposes + replaces + inserts)
	
def edits2(word):
   "All edits that are two edits away from `word`."
   return (e2 for e1 in edits1(word) for e2 in edits1(e1))
   print(correction('speling'))
   print(correction('korrectud'))

在该程序中，我们将在包含已更正单词的“big.txt”中进行匹配。单词与文本文件中包含的单词匹配，并相应地打印适当的结果。

输出

上述代码将生成以下输出 -