Extracting input output variability

shulemsishulemsi Member Posts: 1 Contributor I
edited December 2018 in Help

Hi everyone,

I have a question about how to extract and store the input-output variability in rapidminer.

I am using the iris dataset. 

I want to find the maximum and minimum prediction values observed by varying the value of the input, something like the graph attached. I know we can see the changes using model simulator operator. But, I would like to store the value of maximum and minimum in variables automatically. Is it possible to do that? 


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    IngoRMIngoRM Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, Community Manager, RMResearcher, Member, University Professor Posts: 1,751 RM Founder



    Interesting ask.  Quick question: what is supposed to happen with the other variables while you change one?  Staying constant?  At what value?  Average or mode?  If that is the case, you could in theory do a grid search over the range of each of the attributes, apply the models, collect the confidences and plot them.  It is a bit of process design needed for that, I do not think we have an operator or visualization out of the box for this.








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