The 10th annual MLSP competition: First place
Arno Solin, Simo Särkkä · 2014
The goal of the MLSP 2014 Schizophrenia Classification Challenge was to automatically diagnose subjects with schizophrenia based on multimodal features derived from their magnetic resonance imaging (MRI) brain scans. This challenge took place between June 5 and July 20, 2014, and was organized on Kaggle. We present how this classification problem can be solved in terms of a Bayesian machine learning paradigm known as Gaussian process (GP) classification. The proposed solution achieved an AUC score of 0.928, and it ranked first on the Kaggle private leaderboard.