python 自然语言处理 统计语言建模（1/2）

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一、计算单词频率

例子：生成1-gram，2-gram，4-gram的Alpino语料库的分词样本

---

import nltk  # 1 - gram
from nltk.util import ngrams
from nltk.corpus import alpino
print(alpino.words())
unigrams=ngrams(alpino.words(),1)
for i in unigrams:
    print(i)

---

import nltk  #2 - gram
from nltk.util import ngrams
from nltk.corpus import alpino
print(alpino.words())
bigrams_tokens=ngrams(alpino.words(),2)
for i in bigrams_tokens:
    print(i) 

---

import nltk  #4 - gram
from nltk.util import ngrams
from nltk.corpus import alpino
print(alpino.words())
quadgrams=ngrams(alpino.words(),4)
for i in quadgrams:
    print(i)

生成一段文本的2 - grams 和 2 - grams的频数 以及 4 - grams和4 - grams的频数

---

import nltk  # 2 - grams
from nltk.collocations import *
import nltk
text="Hello how are you doing ? I hope you find the book interesting"
tokens=nltk.wordpunct_tokenize(text)
twograms=nltk.collocations.BigramCollocationFinder.from_words(tokens)
for twogram, freq in twograms.ngram_fd.items():
    print(twogram,freq)

---

import nltk # 4 - grams
from nltk.collocations import *
import nltk
text="Hello how are you doing ? I hope you find the book interesting"
tokens=nltk.wordpunct_tokenize(text)
fourgrams=nltk.collocations.QuadgramCollocationFinder.from_words(tokens)
for fourgram, freq in fourgrams.ngram_fd.items():
    print(fourgram,freq)

二、NLTK的频率

import nltk
from nltk.probability import FreqDist 
text="How tragic that most people had to get ill before they understood what a gift it was to be alive"
ftext=nltk.word_tokenize(text)
fdist=FreqDist(ftext)

print(fdist.N())#总数
print(fdist.max())#数值最大的样本的频率
print(fdist.freq("How"))#频率

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for i in fdist:
    print(i,fdist.freq(i))#输出全部的样本的频率

words=fdist.keys()
print(words)#map中的key

fdist.tabulate()#绘制频数分布图
fdist.plot()

频率、概率之间的关系

在一定的实验情况下频率与概率可以相互替换，比如扔一枚硬币10000次，向上的频数是5023次，概率可以相当于5023/10000，为了获取这些频率之间的分布（概率之间的分布）；我们通常用估计来求解

三、NLTK中的概率分布（在nltk中的probability.py文件中，大家可以去拜读）

我们知道了频率就大概知道了概率，概率论中应该有学过估计，利用样本来求解一些方差、期望。这里使用频率来求解概率分布

import nltk #最大似然估计
from nltk.probability import FreqDist, MLEProbDist   
text="How tragic that most people had to get ill before they understood what a gift it was to be alive"
ftext=nltk.word_tokenize(text)
fdist=FreqDist(ftext)
print(MLEProbDist(fdist).max())
print(MLEProbDist(fdist).samples())
for i in MLEProbDist(fdist).freqdist():
    print(i,MLEProbDist(fdist).prob(i))

import nltk   #Lidstone估计
from nltk.probability import FreqDist, LidstoneProbDist   
text="How tragic that most people had to get ill before they understood what a gift it was to be alive"
ftext=nltk.word_tokenize(text)
fdist=FreqDist(ftext)
print(LidstoneProbDist(fdist,0.5).max())
print(LidstoneProbDist(fdist,0.5).samples())
for i in LidstoneProbDist(fdist,0.5).freqdist():
    print(i,LidstoneProbDist(fdist,0.5).prob(i))

还有其他估计函数可以查看文档 probability