Probability prediction using support vector machines
Reports on an investigation of the use of support vector machines in the problem of beating bookmakers' odds. The method used is to create nine regression lines, one for each of the possible half-time/full-time possibilities, e.g. a draw at half time with the home team winning at full time. We extend the support vector machine by incorporating variable-width permissible error bounds based on our knowledge of the sample size on which each of the data points is based. We show that the variable-width method improves the regression.