Young planets are both relatively rare and also incredibly useful in terms of providing insight into planet formation. Those same planet formation theories are then further helpful in refining our understanding of stellar parameters and our ability to predict different timescales for host stars. The K2 dataset is a suitable starting point because it has observed a number of young clusters that offer information about the ages of numerous stars that would have formed at roughly the same time. Our team has developed an entirely automated planet candidate catalog from 377,163 stars observed by K2. The completeness and the reliability of the catalog has been measured, allowing us to use the catalog to calculate robust occurrence rates. Given a very large quantity of stars observed by K2 in this catalog, will use the BANYAN Sigma analysis tool to assess the probability of cluster membership for each of the stars searched to produce the catalog, which depends on a Bayesian algorithm, to efficiently and more accurately determine cluster membership probabilities for the stars in our catalog. In particular, we are interested to predict timescales and better understand the evolution of planets in the Upper Scorpio, Pleiades, Hyades, and Praesepe clusters that were observed by K2. By using BANYAN Sigma to separate cluster stars from K2 field stars, we will investigate any potential relationships that might exist between stellar age and occurrence rates, while doing so with a completely automated detection process.