Principal Component Analysis (PCA) to reduce the dimensionality of a dataset while preserving as much variance as possible. PCA aims to extract relevant information by identifying principal components that explain the relationships between features in the data.
active 2025-02-05 → 2025-02-05 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 1 days from 2025-02-05 to 2025-02-05. Pushes: 12 total, peak 12 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.
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Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
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.