Multidimensional classifiers for neuroanatomical data

This study explores the benefits of using mul-tidimensional classification. Its novelty lies in the application of state-of-the-art machine learning techniques to the Neuromorpho dataset. We formulate a supervised classification problem for predicting specie, gender, level one cell type, level two cell type, development stage and area of the neocortex based of a set of morphological features extracted from a neuron.