ExoProfiler uses 12 physical variables selected during EDA as the best candidates for capturing orbital, size, thermal, and stellar diversity across the exoplanet population. These variables feed every stage of the pipeline — preprocessing, PCA, and clustering — in a fixed canonical order.Documentation Index
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Variable Selection Rationale
Variables were chosen for their scientific relevance to planetary characterization: orbital architecture, planetary bulk properties, thermal conditions, and host-star properties. Several pairs within the 12 are strongly correlated (for example, stellar radius and stellar mass). These were deliberately retained rather than pre-screened, because PCA is specifically designed to summarize redundant dimensions into orthogonal components. Removing correlated variables before PCA would discard information without adding robustness.Planetary Variables
The seven planetary variables describe each exoplanet’s orbit, physical size, and thermal environment.| Variable | Description | Unit | Transform | Null % |
|---|---|---|---|---|
pl_orbper | Orbital period | days | log1p | 0.11% |
pl_orbsmax | Orbital semi-major axis | AU | log1p | 22.53% |
pl_rade | Planetary radius | Earth radii | log1p | 1.21% |
pl_bmasse | Planetary mass | Earth masses | log1p | 31.76% |
pl_orbeccen | Orbital eccentricity | 0–1 (dimensionless) | none | 31.32% |
pl_insol | Insolation flux (relative to Earth) | S⊕ | log1p | 57.58% |
pl_eqt | Equilibrium temperature | K | none | 26.26% |
Stellar Variables
The five stellar variables describe the host star that each exoplanet orbits. They provide context for orbital stability, habitability, and detection conditions.| Variable | Description | Unit | Transform | Null % |
|---|---|---|---|---|
st_teff | Stellar effective temperature | K | none | 2.53% |
st_rad | Stellar radius | Solar radii | log1p | 0.33% |
st_mass | Stellar mass | Solar masses | none | 13.30% |
st_met | Stellar metallicity | dex | none | 24.51% |
st_logg | Stellar surface gravity (log) | log(cm/s²) | none (already log-scale) | 9.56% |
Transform Decisions
Before scaling, several variables receive alog1p transformation. The logic behind each decision is as follows:
log1p(x)applied topl_orbper,pl_orbsmax,pl_rade,pl_bmasse,pl_insol, andst_rad— these are positive quantities with heavy right-skewed distributions (e.g., orbital periods span fractions of a day to thousands of days). Compressing their range before scaling prevents extreme values from dominating the PCA solution.pl_orbeccenexcluded fromlog1pbecause it is bounded between 0 and 1 and does not exhibit the unbounded right tail that motivates the transform.st_loggexcluded fromlog1pbecause it is already expressed on a logarithmic scale (log cm/s²); applying a second logarithm would distort rather than normalize it.- All 12 variables then pass through
RobustScaler, which centers on the median and scales by the interquartile range. This makes the pipeline robust to physical outliers such as extreme hot Jupiters without deleting or clipping them.
FEATURE_COLUMNS Order
The canonical column order below must be preserved exactly when applying the saved pipeline artifacts (
preprocessing_pipeline.joblib and pca_model.joblib) to new data. Reordering the columns will produce incorrect transformed values and invalid PCA projections.