DocumentCode
3149493
Title
Using neural networks to predict binary outcomes
Author
Ong, Enn ; Flitman, Andrew
Author_Institution
Dept. of Bus. Syst., Monash Univ., Clayton, Vic., Australia
Volume
1
fYear
1997
fDate
28-31 Oct 1997
Firstpage
427
Abstract
Predicting binary outcomes with respect to sports typically involves the use of human judgement and subjectivity. This research considers the use of neural networks and logistic regression as an interesting and quantifiable alternative to human tipsters, whose predictions are of a qualitative nature. Using a set of naive but objective input variables, we highlight the improvement in prediction accuracy obtained through the use of neural networks and logistic regression. A comparison between neural networks, logistic regression and human tipping experts is presented
Keywords
forecasting theory; neural nets; sport; statistical analysis; binary outcome prediction; human judgement; human subjectivity; human tipping experts; logistic regression; naive objective input variables; neural networks; prediction accuracy; qualitative predictions; sport; tipsters; Accuracy; Australia; CD-ROMs; Humans; Information technology; Input variables; Logistics; Neural networks; Predictive models; Statistical analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Processing Systems, 1997. ICIPS '97. 1997 IEEE International Conference on
Conference_Location
Beijing
Print_ISBN
0-7803-4253-4
Type
conf
DOI
10.1109/ICIPS.1997.672816
Filename
672816
Link To Document