https://github.com/oceanthunder/schwiftystudentsml
Implementaion of Random Forest, CNN and FCNN on 'Student Performance Factors' dataset
https://github.com/oceanthunder/schwiftystudentsml
cnn fcnn random-forest student-performance
Last synced: 9 months ago
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Implementaion of Random Forest, CNN and FCNN on 'Student Performance Factors' dataset
- Host: GitHub
- URL: https://github.com/oceanthunder/schwiftystudentsml
- Owner: oceanthunder
- Created: 2024-10-17T10:24:16.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-11-26T11:16:47.000Z (over 1 year ago)
- Last Synced: 2025-06-29T18:03:13.673Z (11 months ago)
- Topics: cnn, fcnn, random-forest, student-performance
- Language: Python
- Homepage:
- Size: 89.8 KB
- Stars: 0
- Watchers: 1
- Forks: 1
- Open Issues: 0
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Become a Schwifty Student
- **CNN-1.py**: Implements a Convolutional Neural Network (CNN) model.
- **CNN-2.py**: Enhances the CNN model from `CNN-1.py` by adding early stopping and learning rate reduction.
- **RandomForest.py**: Implements a Random Forest model.
- **FCNN.py**: Implements a Fully Connected Neural Network (FCNN) model.
- **FeatureImportance.py**: Contains code for sorting and displaying the feature importance in a Decision Tree Regressor.
The dataset, `StudentPerformanceFactors.csv`, was sourced from Kaggle. You can find it [here](https://www.kaggle.com/datasets/lainguyn123/student-performance-factors/data).