Practical Introduction to machine learning for neuroimaging: classifiers, dimensionality reduction, cross-validation and neuropredict. How to apply machine learning to your data, even if you do not know how to program. Learn what is machine learning and get a high-level overview of few popular types of classification and dimensionality reduction methods. Learn (without any math) how support vector machines work. Learn how to plan a predictive analysis study on your own data? What are the key steps of the workflow? What are the best practices, and which cross-validation scheme to choose? How to evaluate and report classification accuracy? Learn which toolboxes to use when, with a practical categorization of few toolboxes. This is followed by detailed demo of neuropredict, for automatic estimation of predictive power of different features or classifiers without needing to code at all.
Enseignant: SciNet Team
Date: : jeu., 27 juin 2019 - 9:30 am