[Python] I am getting error while running this line of code gnb.fit(df_train, y_train)

Title: ValueError: could not convert string to float when training GaussianNB for SMS Spam Detection

Body:
I'm building an SMS spam detection tool and encountering an error while predicting with a GaussianNB model. Here's the error message:

UserWarning: X has feature names, but GaussianNB was fitted without feature names
warnings.warn(
---------------------------------------------------------------------------
ValueError: could not convert string to float: 'Dear i am not denying your words please'


Here’s the relevant part of my code:

from sklearn.naive_bayes import GaussianNB
from sklearn.metrics import accuracy_score, confusion_matrix, precision_score

# Training the model
gnb = GaussianNB()
gnb.fit(df_train, y_train)

# Making predictions
y_pred1 = gnb.predict(df_test) # Error occurs here

# Evaluating the model
print(accuracy_score(y_test, y_pred1))
print(confusion_matrix(y_test, y_pred1))
print(precision_score(y_test, y_pred1))


I suspect the issue is related to the input data format. df_train and df_test contain a column with SMS text, but GaussianNB requires numeric input.

I suspect the issue is related to the input data format. df_train and df_test contain a column with SMS text, but GaussianNB requires numeric input.

Questions:

1. 
   How can I preprocess the text data so that GaussianNB can handle it?
   
   
2. 
   How do I address the warning about feature names (X has feature names, but GaussianNB was fitted without feature names)?
   

Here’s what I’ve tried so far:

• 
  Converting the text data to numeric using TfidfVectorizer. However, I’m not sure if I implemented it correctly.
  
  
• 
  Ensuring no missing values in the dataset using .isnull().sum().
  

Any guidance or suggestions to fix this issue would be greatly appreciated. Thanks in advance!

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