https://github.com/tk04/nlp-email-spam-detector
Used a dataset that already had some emails that were classified as spam or not spam. Then clean up the data and removed punctuation and common stopword. After than, I used some sckit-learn's feature extraction class to apply Count Vectorizer and then Tfidftransform. I then applied sklearn's MultinomialNB classifier on that data. I used that trained model to predict if an email was spam or not on a test data and used sklearn's metrics to see how well my model performed.
https://github.com/tk04/nlp-email-spam-detector
Last synced: about 1 month ago
JSON representation
Used a dataset that already had some emails that were classified as spam or not spam. Then clean up the data and removed punctuation and common stopword. After than, I used some sckit-learn's feature extraction class to apply Count Vectorizer and then Tfidftransform. I then applied sklearn's MultinomialNB classifier on that data. I used that trained model to predict if an email was spam or not on a test data and used sklearn's metrics to see how well my model performed.
- Host: GitHub
- URL: https://github.com/tk04/nlp-email-spam-detector
- Owner: tk04
- Created: 2021-02-15T17:10:57.000Z (over 5 years ago)
- Default Branch: main
- Last Pushed: 2021-02-16T19:32:18.000Z (over 5 years ago)
- Last Synced: 2025-02-24T10:19:06.038Z (over 1 year ago)
- Language: Jupyter Notebook
- Homepage:
- Size: 536 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0