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Thanks very much for getting back. I’ve tried your approach and am now testing it out by following the example in the SimpleDimmerChained solution.
A follow-up question: One of the inputs to the fuzzy model is a machine-learned model for activity recognition (stationary, walking, running etc.). Now, if I simply take the highest confidence value from the output of the machine-learned model (e.g. stationary with 0.75) and pass it in as the input to the fuzzy model, I obviously lose a significant degree of precision where the other activity confidence degrees (e.g. walking 0.2, running 0.05) are not represented in the input variable to the fuzzy model.
How can I achieve this in fuzzylite i.e. how can I pass in a membership function (e.g. stationary 0.75, walking 0.2, running 0.05) as an input variable? What membership function would accurately represent this type of an input?