python - How can we use Pre-trained model to predict only one new_test_data on any model

Question

Problem Statement :
Data consists of 10000 rows and 3 columns as "tweet","tweet_tokens","sentiment"
This data is from nltk.corpus import twitter_samples

Sample data how it looks like :

shape : (10000, 3)

Used model : MultibinomialNB to train and predict the dataset with CountVectorizer(ngram=(1,1)) and got the following scores :
Precision : 0.771 / Recall : 0.698 / Accuracy : 0.745

Features what it looks like in dataframe :

Saving the model with pickle and predicting it for ONE tweet returns ERROR

Problem : Can we use this trained model to predict just one tweet and output as "Positive" or "Negative" ?? Tried using this model but ends up always as dimension mismatch or shape not aligned

Question : Do we always have to make new_test_data shape as of trained_data_set ??

Answer 1

等待大神答复