Attentional focus training by boundary region data selection
D.T. Davis, Jenq–Neng Hwang · 2003
An attempt is made to improve the classification performance of a trained multilayer perceptron. Using inversion to locate boundary points of the partially trained classification surfaces, the authors have defined boundary regions and selected those training data which fell within the boundary regions. Continuing the training with only the boundary region data, the authors improved classification performance by 6% in an automated cytological classification application.>