如何从tfidf_vectorizer查看TF-IDF值？

from sklearn.feature_extraction.text import TfidfVectorizer

tfidf_vectorizer = TfidfVectorizer()

tfidf_matrix = tfidf_vectorizer.fit_transform(text_data)

tfidf_value = tfidf_matrix[row_index, feature_index]

feature_names = tfidf_vectorizer.get_feature_names()

from sklearn.feature_extraction.text import TfidfVectorizer

# 创建TfidfVectorizer对象
tfidf_vectorizer = TfidfVectorizer()

# 文本数据
text_data = ['This is the first document.',
             'This document is the second document.',
             'And this is the third one.',
             'Is this the first document?']

# 将文本数据转换为TF-IDF矩阵
tfidf_matrix = tfidf_vectorizer.fit_transform(text_data)

# 获取TF-IDF矩阵中的特定值
row_index = 0
feature_index = 1
tfidf_value = tfidf_matrix[row_index, feature_index]
print("TF-IDF value:", tfidf_value)

# 获取特征（词）列表
feature_names = tfidf_vectorizer.get_feature_names()
print("Feature names:", feature_names)