An ensemble ML framework achieves 90.7% morphology classification accuracy and R² values of 0.77–0.92 for key parameters on held-out test data, with external validation against OGLE and Kepler catalogs.
M., S´ anchez-Fern´ andez, C., & Gim´ enez,´A
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Is the `Known' Enough? An Integrated Machine Learning Framework for Eclipsing Binary Classification and Parameter Estimation Based on Well-Characterized Systems
An ensemble ML framework achieves 90.7% morphology classification accuracy and R² values of 0.77–0.92 for key parameters on held-out test data, with external validation against OGLE and Kepler catalogs.