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Home
Python 3
Predicting a Single Review

Predicting a Single Review

Predicting a Single Review
Example Review
Clean the Review
Convert to TF-IDF
Predict the Review
Display the Result

Predicting a Single Review

One of the main goals of this project is to classify new reviews that were not part of the training dataset.

We first preprocess the review, convert it into TF-IDF features, and then use the trained model to predict whether it is fake or genuine.

Example Review

sample_review = "This product is amazing and worth every penny."

Clean the Review

sample_review = clean_text(sample_review)
sample_review = remove_stopwords(sample_review)
sample_review = lemmatize_text(sample_review)

Convert to TF-IDF

sample_vector = tfidf.transform([sample_review])

Predict the Review

prediction = model.predict(sample_vector)
prediction

Display the Result

if prediction[0] == 1:
print("Prediction: Fake Review")
else:
print("Prediction: Genuine Review")

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Predicting a Single Review

Contents

Predicting a Single Review

Example Review

Clean the Review

Convert to TF-IDF

Predict the Review

Display the Result

Fake Review Detection System using Machine Learning

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