There are a lot of machine learning options in R: https://cran.r-project.org/web/views/MachineLearning.html
It sounds like you need to back up a step, and do some reading on the statistical underpinnings of machine learning before you try to figure out how to implement a particular method. There are an enormous number of references online, from brief articles to full courses. Here's one possible starting point: https://statweb.stanford.edu/~tibs/ElemStatLearn/ The options are far too complex and numerous for anyone here to be able to tell you the "right method" to use. Sarah On Tue, Jan 3, 2017 at 12:15 PM, Chuck Snell <chuck.snell.em...@gmail.com> wrote: > Hello, > > I am new to R, a computer programmer friend of mine recommended R for a > project I have on my plate. > > (He is not a R guy but knows I need to consider it for the problem I > described to him) > > Frist, I have plenty of data > > I have been doing this task with regression models but was asked to try to > improve my accuracy. > > I am forecasting an "output" which is numerical based upon forecasted > weather. > > for extreme weather and stable weather my regression does decent. Meaning, > really cold and hot weather that has been cold or hot for a while. > > What I miss is when things change, meaning if we have had mild weather then > a sudden change, intuitively we know things won't behave as if it had been > cold (or hot) for the last week or so but my regression obviously does not > consider the "history" or patterns. > > What was suggested to me was consider some machine learning to identify the > patterns and so forth. > > I have R installed and started searching around the libraries - seems > overwhelming. > > I have found an example of machine learning for R that did "categories" - > maybe of flowers not sure. > > What I need is not categories but a number for an estimate / forecast, > > Can you recommend some routines / libraries / techniques to consider? > > Thanks > -- Sarah Goslee http://www.functionaldiversity.org ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.