在NLTK中选择哪种分类器

import nltk
from nltk.corpus import stopwords
from nltk.tokenize import word_tokenize
from nltk.stem import PorterStemmer
from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer

# 导入数据集
data = ["I love to eat pizza.", "I hate to eat pizza."]

# 对数据集进行预处理，包括分词、去停用词、词干提取等
stop_words = set(stopwords.words("english"))
p_stemmer = PorterStemmer()

for d in data:
    tokens = word_tokenize(d.lower())
    tokens = [p_stemmer.stem(t) for t in tokens if t.isalpha() and t not in stop_words]
    print(tokens)