Abstract
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
Citations
IRE Journals:
Saachi Sawant "Exoplanet Detection Using Machine Learning" Iconic Research And Engineering Journals Volume 9 Issue 8 2026 Page 87-93 https://doi.org/10.64388/IREV9I8-1714036
IEEE:
Saachi Sawant
"Exoplanet Detection Using Machine Learning" Iconic Research And Engineering Journals, 9(8) https://doi.org/10.64388/IREV9I8-1714036
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