https://github.com/johnkou97/titanic
https://github.com/johnkou97/titanic
classification data-science kaggle machine-learning python regression supervised-learning titanic-kaggle xgboost
Last synced: 2 months ago
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- Host: GitHub
- URL: https://github.com/johnkou97/titanic
- Owner: johnkou97
- Created: 2023-07-13T20:22:06.000Z (about 3 years ago)
- Default Branch: master
- Last Pushed: 2023-07-18T13:06:28.000Z (almost 3 years ago)
- Last Synced: 2025-09-10T23:15:41.486Z (10 months ago)
- Topics: classification, data-science, kaggle, machine-learning, python, regression, supervised-learning, titanic-kaggle, xgboost
- Language: Python
- Homepage: https://koutalios.space/projects/kaggle/
- Size: 2.93 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Titanic Challenge - Kaggle
## Introduction
In this challenge, we will try to predict if a passenger survived or not during the Titanic disaster. The dataset is available on [Kaggle](https://www.kaggle.com/c/titanic/data). We use three different models : Logistic Regression from the scikit-learn library, XGBoost and LightGBM.
## Files
`LogReg.py` : Logistic Regression model
`XGBoost.py` : XGBoost model
`LightGBM.py` : LightGBM model
## Results
| Model | Accuracy |
| --- | --- |
| LightGBM | 0.77511 |
| XGBoost | 0.77511 |
| Logistic Regression | 0.76794 |