The multi-surface method (MSM) is a form of decision making using the concept of piecewise-linear separability of datasets to categorize data.
Contents
Introduction
Two datasets are linearly separable if their convex hulls do not intersect. The method may be formulated as a feedforward neural network with weights that are trained via linear programming. Comparisons between neural networks trained with the MSM versus backpropagation show MSM is better able to classify data. The decision problem associated linear program for the MSM is NP-Complete.
Mathematical Formulation
Given two finite disjoint point sets