Reputation: 8014
I am using Python
I have this code that analyse Text documents
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)
I know that TF-IDF assigns a value to each word.
Is there a way that let me see what are the values of inside xtrain_tfidf
?
Upvotes: 0
Views: 521
Reputation: 779
Here is an example
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)
Upvotes: 1