Exoplanet Explorer

NASA ML Dashboard

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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 more

Model Performance Metrics

Ensemble Performance

Best Results
92.20%
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.

Drop your file here or click to browse

Supported formats: CSV, TXT, XLSX (max 5MB)

The sample dataset loads 50 random exoplanets from NASA's TESS dataset

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