Wine reviews used to determine the type of wine training on imbalanced data using classification algorithms like SVM, Naive Bayes and Random Forest Classifier. Neural Network (CNN, RNN and LSTM) and LLM models (DistilBERT and RoBERTa) were also used followed by error analysis using SHAP.
active 2024-08-06 → 2024-10-11 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 67 days from 2024-08-06 to 2024-10-11. Pushes: 8 total, peak 8 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: 1 total, peak 1 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 |
|---|---|---|---|---|
| anurima-saha | 8 | 8 | 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 — 1 stars here means stars gained during the window, not the repo's star count.