Toxic Comment Classification employs Naive Bayes, Logistic Regression, KNN, and Decision Trees to identify harmful content in tweets. The project features a user-friendly web interface using FastAPI and Streamlit, enhancing accessibility for users to assess and manage toxic comments efficiently.
active 2024-01-13 → 2024-01-14 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 2 days from 2024-01-13 to 2024-01-14. Pushes: 7 total, peak 6 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 0 total, peak 0 in a day.
- Pushes
- Pull requests
- Issues
- Comments
- Stars
Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| Raghavgali | 7 | 7 | 0 | 0 |
Recent activity
Latest issues, pull requests and releases
No issue or PR events — this repo's activity is pushes only.
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 0 stars here means stars gained during the window, not the repo's star count.