machine learning goal (new to R )
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.email at 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