Coeus — Kepler Exoplanet Classification

• Explored and cleaned NASA’s Kepler Objects of Interest (KOI) dataset.
• Analysed 6,816 observations containing planetary candidates and false positives.
• Selected 10 numerical features, including orbital period, transit duration, transit depth, planetary radius, and stellar properties.
• Built a logistic regression model to classify planetary candidates and false positives.
• Evaluated model performance using accuracy, precision, recall, F1-score, and a confusion matrix.
• Investigated the effects of classification thresholds on candidate detection.
• Visualised transit depth against orbital period to examine patterns and overlap between the two classes.
• Identified limitations caused by class imbalance and overlapping feature distributions.
• Worked on interpreting predictions cautiously, recognising that classification does not confirm the existence of an exoplanet.