Galaxies evolve in various aspects. Historically, properties that characterize galaxy evolution were chosen based on researchers' scientific intuition. Since we have an overwhelmingly large amount of new datasets, now it is a good moment to reconsider "galaxy evolution". We propose some methods to extract the evolutionary features of galaxies through machine learning. We will show that such methods automatically reproduce important characteristics of galaxies such as the classical active/passive galaxy dichotomy etc.