GA: Machine learning for membership determination in open clusters – Hasan

Membership of stars in clusters is very crucial in parameter determination and studies of clusters. We compare results obtained using supervised and unsupervised methods with Gaia DR2 and EDR3 data. We shall provide insights in to what are the suitable methods to be used and compare results using Gaussian Mixture Models and DBScan as well as Random Forest. We shall highlight the importance of machine learning especially in the study of faint cluster members which can enrich color-magnitude diagrams as well as IMF studies.