https://github.com/mugambi645/wine-quality-classifier
Wine quality prediction with xgboost library
https://github.com/mugambi645/wine-quality-classifier
confusion-matrix gradient-boosting gradient-descent weak-learners wine-quality xgboost xgboost-classifier
Last synced: 2 months ago
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Wine quality prediction with xgboost library
- Host: GitHub
- URL: https://github.com/mugambi645/wine-quality-classifier
- Owner: Mugambi645
- Created: 2024-11-22T14:59:25.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2024-11-25T20:25:57.000Z (6 months ago)
- Last Synced: 2025-01-28T16:16:08.214Z (4 months ago)
- Topics: confusion-matrix, gradient-boosting, gradient-descent, weak-learners, wine-quality, xgboost, xgboost-classifier
- Language: Jupyter Notebook
- Homepage:
- Size: 94.7 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# wine-quality-classifier
- Wine quality classifier using xgboost library.
- XGBoost builds models by combining weak learners (decision trees) into a strong learner through an additive process, optimizing the model using gradient descent.
- Confusion matrix to compute accuracy
- You need basic understanding of vector calculus, partial derivatives and gradient descent for a conceptual understanding of gradient boosting