由于无法转换字符串而无法建模

Question

当我尝试运行以下代码时，出现错误“无法将字符串转换为浮点数”，当我尝试使用代码X_test = [x_test中的x的float（x）来修复它时，我得到了相同的错误] 。如何解决该错误，以便我可以运行模型？

from sklearn.model_selection import train_test_split
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.feature_extraction.text import TfidfTransformer
from sklearn.naive_bayes import MultinomialNB


X_train, X_test, y_train, y_test = train_test_split(df['text'], 
df['Target'], random_state = 0)

count_vect = CountVectorizer()

X_train_counts = count_vect.fit_transform(X_train)

tfidf_transformer = TfidfTransformer()

X_train_tfidf = tfidf_transformer.fit_transform(X_train_counts)



clf = MultinomialNB().fit(X_train_tfidf, y_train)

y_pred = clf.predict(X_test)