Published November 4, 2025
| Version 1.0.0
Software
Open
Exoplanet Detection ML: Detection of Exoplanets with Machine Learning Techniques through Transit Light Curve Analysis
Creators
Description
Exoplanet Detection ML is a machine learning project dedicated to the detection of exoplanets using transit survey-based light curves. By leveraging advanced machine learning algorithms and feature engineering techniques, this project aims to enhance the accuracy and efficiency of exoplanet discovery.
Features
- Automated Exoplanet Detection: Utilizes transit survey-based light curves to identify potential exoplanets.
- Advanced Algorithms: Implements state-of-the-art machine learning models for high accuracy.
- Feature Engineering: Employs robust feature extraction and selection techniques to enhance model performance.
- Dimensionality Reduction: Reduces feature space complexity while preserving essential information.
Machine Learning Algorithms
Exoplanet ML employs a variety of machine learning algorithms to ensure comprehensive analysis and accurate predictions:
- Random Forest Classifier
- LightGBM
- AdaBoost
- Histogram Gradient Boosting
- XGBoost
- XGBoost Calibrated
Below are some examples of model performance:
Model Performance
| Machine Learning Models | Accuracy | Precision | Sensitivity | F1-Score | ROC-AUC Score |
|---|---|---|---|---|---|
| Random Forest | 84% | 85% | 84% | 83% | 85% |
| Adaptive Boosting | 82% | 82% | 82% | 80% | 86% |
| Histogram Gradient Boosting | 87% | 87% | 87% | 87% | 96% |
| Extreme Gradient Boosting | 86% | 87% | 86% | 85% | 95% |
| Extreme Gradient Boosting (Calibrated) | 89% | 89% | 89% | 89% | 93% |
Resources
Dimensionality Reduction
- Introduction to PCA, t-SNE, and UMAP
- Plotly t-SNE and UMAP Projections
- Kernel PCA in scikit-learn
- Understanding UMAP
- UMAP Documentation
TsFresh Feature Selection
Scikit-Learn Supervised Learning List and Description
Gaussian Process
Scikit-Learn Unsupervised Learning List and Description
Hyperopt Hyperparameter Tuning
Incremental Principal Component Analysis
Scikit-Learn Plotting
Probability Calibration
Technical Problem Solution and Miscellaneous Links
Acknowledgements
- Feature Engineering with TSFresh
- Exoplanet Archive Acknowledgements
- Exoplanet Archive DOI
- Exoplanet Archive Table View
- Exoplanet Archive Table Redirect
License
This project is licensed under the CC-BY-4.0.
Full Changelog: https://github.com/mirsakhawathossain/Exoplanet-Machine-Learning/commits/1.0.0
Files
mirsakhawathossain/Exoplanet-Machine-Learning-1.0.0.zip
Files
(114.1 MB)
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Additional details
Related works
- Is supplement to
- Software: https://github.com/mirsakhawathossain/Exoplanet-Machine-Learning/tree/1.0.0 (URL)