mohamedraslan25/OverFitting-UnderFitting-Lasso-Ridge-Regression
View on GitHub ↗Related repositories →📚 Overfitting, Underfitting, Lasso & Ridge Regression 🚀 This project explores Overfitting (high variance) and Underfitting (high bias) in machine learning. Lasso Regression (L1) reduces overfitting by eliminating irrelevant features, while Ridge Regression (L2) shrinks coefficients. Both techniques enhance model generalization and performance.
active 2024-10-09 → 2024-10-09 (UTC)
Activity over time
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Line chart, 1 days from 2024-10-09 to 2024-10-09. Pushes: 2 total, peak 2 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
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| mohamedraslan25 | 2 | 2 | 0 | 0 |
Recent activity
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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.