Diagnosing ADHD by MR images using meta-cognitive radial basis function network - Praveena Satkunarajah (2014)
The purpose of this experiment is to explore two different feature selection methods, the T-test and Spectral Feature Selection, on the training data, so that the features that are more crucial and contribute most to detecting whether a child has ADHD can be extracted and used to train the Meta-cognitive Radial Basis Function Network (McRBFN). Feature selection helps to reduce the dimensionality of the data and sheds features that are irrelevant to the learning process.