How sakshi01coder/fake-product-review-detection works
This is a notebook-based fake product review classifier. Its documented user workflow accepts a review, preprocesses text with cleaning and TF-IDF, then predicts whether it is fake or genuine. A separate branch compares classifiers using standard metrics. The README describes labeled training data, while the tree also lists dataset.csv; without notebook excerpts, their exact wiring and implementation details cannot be verified.
Main entry points: A035,A044_MLA_Project .ipynb Review classifier · dataset.csv Labeled reviews
Components 6
Review workflow
- Text preprocessing
A035,A044_MLA_Project .ipynb - Fake or genuine
A035,A044_MLA_Project .ipynb
Modeling and evaluation
- Review classifier
A035,A044_MLA_Project .ipynb - Model evaluation
A035,A044_MLA_Project .ipynb
Review data
- Labeled reviews
dataset.csv
Other components
- Review submitter
Connections 5
- Review submitter → Text preprocessing: submits review
- Text preprocessing → Review classifier: transforms text
- Review classifier → Fake or genuine: predicts label
- Labeled reviews → Review classifier: training data
- Review classifier → Model evaluation: compared by