Theoretical foundations of spectroscopic feature extraction in AstroSpectro: the Physics-Informed approach, the 6 descriptor families, spectro_only mode, and a SHAP check of how much of the model's attribution comes from physical features.
AstroSpectro's most important metrics and scientific findings.
AstroSpectro results in two separate studies: unsupervised dimensionality reduction (PCA, UMAP, t-SNE, HDBSCAN) on the PHY-3500 dataset (G1, 43,019 spectra), and the reference XGBoost classifier with its SHAP attribution on the 350k-spectrum generation (G2, run v6, which includes Gaia/photometric features).
SHAP analysis of the AstroSpectro XGBoost classifier — the central scientific finding.