Python 如何从tfidf_矢量器中查看TF-IDF值?
我正在使用Python 我有一个分析文本文档的代码Python 如何从tfidf_矢量器中查看TF-IDF值?,python,nlp,tf-idf,tfidfvectorizer,Python,Nlp,Tf Idf,Tfidfvectorizer,我正在使用Python 我有一个分析文本文档的代码 tfidf_vectorizer = TfidfVectorizer(max_df=0.8, max_features=10000) # split dataset into training and validation set xtrain, xval, ytrain, yval = train_test_split(movies_new['clean_plot'], y, test_size=0.2, random_state=9)
tfidf_vectorizer = TfidfVectorizer(max_df=0.8, max_features=10000)
# split dataset into training and validation set
xtrain, xval, ytrain, yval = train_test_split(movies_new['clean_plot'], y, test_size=0.2, random_state=9)
# create TF-IDF features
xtrain_tfidf = tfidf_vectorizer.fit_transform(xtrain)
xval_tfidf = tfidf_vectorizer.transform(xval)
我知道TF-IDF为每个单词赋值
有没有办法让我看看xtrain\u tfidf
内部的值是什么?下面是一个例子
from sklearn.feature_extraction.text import TfidfVectorizer
import pandas as pd
vect = TfidfVectorizer()
tfidf_matrix = vect.fit_transform(documents)
df = pd.DataFrame(tfidf_matrix.toarray(), columns = vect.get_feature_names())
print(df)
我发现,如果您正在尝试您的示例,您应该使用
tfidf\u矢量器
。我给出的代码只是一个示例。请相应地更改变量