Advanced Exploration

For advanced users, PATHFINDER AI offers customization options to enhance its performance. You can tweak noise thresholds in config.yaml to suit stars with high variability or retrain the deep learning model with custom TESS data via:

python train_model.py --data new_data.csv --epochs 50

Custom visualizations are achievable with:

python visualize.py --input output/results.csv --type folded

Fine-tuning Fourier analysis can target specific orbital periods by adjusting fourier_settings.yaml.