This repository contains an XGBoost machine learning model for detecting exoplanets using NASA Kepler mission data.
1import joblib
2import xgboost as xgb
3import numpy as np
4
5# Load the model
6arte = joblib.load("exoplanet_xgb.joblib")
7model = arte["model"]
8features = arte["features"]
9
10# Make predictions
11# Prepare your data with the required features
12X = np.array([...]) # Your feature values in the correct order
13dmat = xgb.DMatrix(X, feature_names=features)
14predictions = model.predict(dmat)
This model is also available via a FastAPI server. See the repository for app.py.
1pip install -r requirements.txt
2uvicorn app:app --host 0.0.0.0 --port 8000
This model uses publicly available NASA Kepler data.
