no code implementations • 13 Oct 2020 • Kojo Sarfo Gyamfi, James Brusey, Elena Gaura
We propose a differential radial basis function (RBF) network termed RBF-DiffNet -- whose hidden layer blocks are partial differential equations (PDEs) linear in terms of the RBF -- to make the baseline RBF network robust to noise in sequential data.
no code implementations • 24 Mar 2017 • Kojo Sarfo Gyamfi, James Brusey, Andrew Hunt
Moreover, the difficulty in parameter selection in the existing TS approach does not make it any more attractive.
no code implementations • 24 Mar 2017 • Kojo Sarfo Gyamfi, James Brusey, Andrew Hunt, Elena Gaura
Under normality and homoscedasticity assumptions, Linear Discriminant Analysis (LDA) is known to be optimal in terms of minimising the Bayes error for binary classification.