Code to predict empirically the properties of galaxies given dark matter halo properties. Several supervised learning algorithms have been employed : Random Forest, Support Vector Machine, Stochastic Gradient Decent, and Neural Network. Dimensionality reduction using PCA and local linear embedding also have been considered. This is part of my (final) project in Machine Learning in astrophysics course.
Data set : galaxy_halo_cat.tar.gz
Course website : Machine Learning in Astrophysics