Revealing posturographic profile of patients with Parkinsonian syndromes through a novel hypothesis testing framework based on machine learning

Fig 7

The average performance of two-sample testing approaches in simulated datasets with class balance 50/50, and 10, 20, or 30 features.

We observe that ts-AUC and MMD have almost the same performance and always superior to the multiple testing strategies.