https://github.com/bell-kevin/titanicneuralnetwork
XGBoost, which tends to be one of the top-performing algorithms for structured/tabular data. We do some feature engineering (e.g., extracting titles from passenger names, creating family size features, etc.), then train and tune an XGBoost model
https://github.com/bell-kevin/titanicneuralnetwork
machine-learning neural-network titanic titanic-dataset titanic-kaggle titanic-survival-prediction
Last synced: 4 months ago
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XGBoost, which tends to be one of the top-performing algorithms for structured/tabular data. We do some feature engineering (e.g., extracting titles from passenger names, creating family size features, etc.), then train and tune an XGBoost model
- Host: GitHub
- URL: https://github.com/bell-kevin/titanicneuralnetwork
- Owner: bell-kevin
- License: agpl-3.0
- Created: 2024-12-29T05:30:34.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2024-12-29T15:58:40.000Z (6 months ago)
- Last Synced: 2025-02-22T05:11:28.245Z (4 months ago)
- Topics: machine-learning, neural-network, titanic, titanic-dataset, titanic-kaggle, titanic-survival-prediction
- Language: Jupyter Notebook
- Homepage:
- Size: 45.9 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0