Postulating exoplanetary habitability via a novel anomaly detection method

A profound shift in the study of cosmology came with discovery thousands exoplanets and possibility existence billions them our Galaxy. The biggest goal these searches is whether there are other life-harbouring planets. However, question which detected planets habitable, potentially-habitable, or maybe even inhabited, still not answered. Some potentially habitable have been hypothesized, but since Earth only known planet, measures habitability necessarily determined as reference. Several recent works introduced new metrics based on optimization methods. Classification using supervised learning another emerging area study. both modeling approaches suffer from drawbacks. We propose an anomaly detection method, Multi-Stage Memetic Algorithm (MSMA), to detect anomalies extend it unsupervised clustering algorithm MSMVMCA use anomalies. postulate that anomaly, few among data points. describe MSMA-based approach a novel distance function candidates (including Earth). results cross-matched exoplanet catalog (PHL-HEC) Planetary Habitability Laboratory (PHL) optimistic conservative lists exoplanets.