Apply model to unlabelled data and writing a csv

Jackinw97

So, I have a dataset which I am splitting to train on using cross validation, and I get my results and performance for this all fine, but then I have to apply this model to unlabelled data and export the predictions to a csv (obviously no performance measure here because it's unlabelled). But, after I have done the training part, how do I actually apply that to the unlabelled data? I am pretty new to rapidminer and would love some help. Thanks. 

kayman

Not sure what you already did so I might be stating the obvious, but typically an oversimplified workflow looks like this : 

1. You train a model and save this model using store output.
2. You take this output (saved model) and use the apply model operator. The model goes to the mod input port, the new data to the unl port (unlabeled). 
3. The output should now contain your predictions. This output can then be saved as cvs using the export cvs operator.