问如何将字符串中的ngram和词频转换为向量，以构建SVN模型

EN

import nltk
from collections import Counter
from nltk import ngrams
from nltk.stem import WordNetLemmatizer


# lowercase, remove punctuation, and lemmatize string
def word_generator(str):
    wnl = WordNetLemmatizer()
    clean = nltk.word_tokenize(str)
    words = [wnl.lemmatize(word.lower()) for word in clean if word.isalpha()]
    for word in words:
        yield word


# create list of freqs
def freq_count(str):
    voc_freq = Counter()
    for word in word_generator(str):
        voc_freq[word] += 1
    trimmed = sorted(voc_freq.items(), reverse=True, key=lambda x: x[1])
    return trimmed


# create n-grams
def make_ngrams(str, n):
    grams = ngrams([word for word in word_generator(str)], n)
    return list(grams)

>>> my_str = 'This is this string, not A great Strings not the greatest string'

>>> print(freq_count(my_str))
[('string', 3), ('this', 2), ('not', 2), ('is', 1), ('a', 1), ('great', 1), ('the', 1), ('greatest', 1)]

>>> print(make_ngrams(my_str, 4))
[('this', 'is', 'this', 'string'), ('is', 'this', 'string', 'not'), ('this', 'string', 'not', 'a'), ('string', 'not', 'a', 'great'), ('not', 'a', 'great', 'string'), ('a', 'great', 'string', 'not'), ('great', 'string', 'not', 'the'), ('string', 'not', 'the', 'greatest'), ('not', 'the', 'greatest', 'string')]