Ensembles of Classifiers for Morphological Galaxy Classification

We compare the use of three algorithms for performing automated morphological galaxy classification using a sample of 800 galaxies. Classifiers are created using a single training set as well as bootstrap replicates of the training set, producing an ensemble of classifiers. We use a Naive Bayes classifier, a neural network trained with backpropagation, and a decision-tree induction algorithm with pruning. Previous work in the field has...