Exoplanet Detection Using Machine Learning

The detection of exoplanets plays a crucial role in understanding planetary systems beyond our solar system. Traditional detection techniques often require extensive manual verification, making automated solutions desirable. In this study, a machine learning–based approach for exoplanet detection is proposed using data from the NASA Kepler mission. After preprocessing and feature selection, a Random Forest classifier is trained to distinguish confirmed exoplanets from false positives. Experimental results demonstrate that the proposed model achieves an accuracy of 99.29