This project aims to analyze the sentiment of reviews by implementing a review polarity classification system. I will compare the performance of three different feature representations, namely Bag of Words, TFIDF, and Word2Vector using KNN Algorithms
active 2024-06-07 → 2024-07-27 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 51 days from 2024-06-07 to 2024-07-27. Pushes: 0 total, peak 0 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
Nobody pushed, opened or commented here in the loaded window — this repo's activity is stars and forks only.
Recent activity
Latest issues, pull requests and releases
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.