There are multiple marketing models in place to predict individual-level probabilities of whether or not someone would respond to a solicitation, whether or not they would become a customer, and if they did become a customer, how much money the company is likely to make. Each individual receives a score from each model, and the final goal is to rank all individuals based on a final score. As long as multiple models exist, I'm guessing the method of deriving a final score from multiple model scores is an optimization algorithm.
I have no experience with optimization in R, and was wondering if anyone could recommend a package or function, or any other method, for this particular type of problem. Thanks. -- View this message in context: http://www.nabble.com/Optimizing-Multiple-Models...any-suggestions--tp21979556p21979556.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.
