ML Model Prediction
Select model and upload data for exoplanet classification
Required Columns for TESS Model (16 total)
ra
dec
st_teff
st_logg
st_rad
st_dist
st_pmra
st_pmdec
st_tmag
pl_orbper
+6 moreModel Performance Metrics
Ensemble Performance
Best Results92.20%
Accuracy
Overall prediction correctness
92.09%
Precision
Positive prediction accuracy
92.20%
Recall
Actual positives found
92.06%
F1-Score
Balanced performance measure
Individual Model Performance
XGBoost
Gradient Boosting
Accuracy91.84%
Precision
92.1%
Recall
92.2%
F1
92.1%
LightGBM
Gradient Boosting
Accuracy92.52%
Precision
92.1%
Recall
92.2%
F1
92.1%
CatBoost
Gradient Boosting
Accuracy89.99%
Precision
92.1%
Recall
92.2%
F1
92.1%
Why Ensemble?
The ensemble model combines predictions from all three algorithms using weighted voting (40% CatBoost, 35% XGBoost, 25% LightGBM). This approach leverages the strengths of each model to achieve higher accuracy and more reliable predictions than any single model alone.
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Supported formats: CSV, TXT, XLSX (max 5MB)
The sample dataset loads 50 random exoplanets from NASA's TESS dataset
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