# Ghentlesteve/wine-quality-svc-tuning

> An educational Jupyter notebook: classifying Vinho Verde wine quality with an SVC and grid-search hyperparameter tuning, showing why accuracy is misleading on imbalanced data.

- Magnitude: 0.6 out of 10 — Quiet
- Stars: 2 total · +2 stars today, ≈ 3 by evening
- Star trust: star growth looks organic
- Category: Learning & lists · Language: Jupyter Notebook · Created: 2026-09-28 · Last push: 2026-09-28
- GitHub: https://github.com/Ghentlesteve/wine-quality-svc-tuning · Page: https://gitnova.dev/en/r/Ghentlesteve/wine-quality-svc-tuning

## Useful for

- Reproduce the class-imbalance analysis on the Wine Quality dataset
- Compare a baseline SVC with a grid-searched model via accuracy and confusion matrices
- Reuse the custom log-loss scoring function example for SVC

## Why it’s here

- 2 stars so far today, about 3 expected by the end of the day.
- The repository is 1 day old and already has 2 stars. With less than two weeks of history, there's no usual pace to compare the spike against yet.

## Star trust

Star growth looks organic.

Star-trust labels are heuristics based on the repository’s behavior, not a check of every stargazer.

## Numbers

- Forks: 132
- Issues and pull requests: 0
- Watchers: 2
- Average over the last week: 1 per day
- Usual pace: too little history (under two weeks)
- Stars in the last hour (measured): -115

## Stars per day, last 3 days (oldest → newest, today is partial)

2026-09-27 … 2026-09-29: 0, 0, 2

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Magnitude (0–10) measures how fast and how unusually interest in a repository is growing right now. It is not a quality score.
Days are UTC. “So far today” is a fact; “expected by the end of the day” is a forecast.
Summaries and use cases are written by an LLM (DeepSeek V4.1 Flash) from the README and may be inaccurate: verify specific claims (benchmarks, speed, hardware) in the repository itself.
Data as of 2026-09-29 14:30 UTC, updated every 30 minutes.