I am attempting to develop an Azure ML experiment that uses R to perform predictions of a continuous response variable. The initial experiment is relatively simple, incorporating only a few experiment items, including "Create R Model", "Train Model" and "Score Model", along with some data input.
I have written a training script and a scoring script, both of which appear to execute without errors when I run the experiment within ML Studio. However, when I examine the scored dataset, the score values are all missing values. So I am concerned that my scoring script could be returning scores incorrectly. Can anyone advise what type I should be returning? Is it meant to be a single column data.frame, or something else?
It is also possible that my scores are not being properly calculated within the scoring script, although I have run the training and scoring scripts within R Studio, which shows the expected results. It would also be helpful if someone could suggest how to perform debugging of my scoring script in some way, so that I could determine whereabouts the code is failing to behave as expected.
Thanks, Paul
Try using this sample and compare with yours - https://gallery.cortanaintelligence.com/Experiment/Compare-Sample-5-in-R-vs-Azure-ML-1