Probability prediction using support vector machines

Author

McKay, Duncan ; Fyfe, Colin

Author_Institution

Appl. Comput. Intelligence Res. Unit, Paisley Coll. of Technol., UK

Volume

1

fYear

2000

fDate

2000

Firstpage

189

Abstract

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

Keywords

errors; forecasting theory; learning automata; probability; sport; bookmakers´ odds; data points; half-time/full-time possibilities; probability prediction; regression lines; sample size; support vector machines; variable-width permissible error bounds; Analysis of variance; Computational intelligence; Data analysis; Extremities; Intelligent systems; Learning systems; Machine learning; Smoothing methods; Support vector machine classification; Support vector machines;

fLanguage

English

Publisher

ieee

Conference_Titel

Knowledge-Based Intelligent Engineering Systems and Allied Technologies, 2000. Proceedings. Fourth International Conference on

Conference_Location

Brighton

Print_ISBN

0-7803-6400-7

Type

conf

DOI

10.1109/KES.2000.885789

Filename

885789