Hi I am trying to use various techniques (eg svm, logistic regression, neural networks) to classify and predict the outcome of horse races.
Most of my predictive features are categorical - horse, jockey, trainer - and I keep on running out of memory owing to the size of the vector. Does anyone know how to solve the problem? I have classified the outcomes as win/lose or place/lose with a view to train on x years of results and then testing on the subsequent years results. Is there some alternate way of looking at the problem? Does anyone have pointers to published work in this area? Thanks. Stephen ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
