Hi,
I am designing an App that utilizes a Random Forest & Nearest Neighbor Model to give a predicted Net Revenue value & nearest comparisons for some input data.
The model works great (yay Alteryx), but I am wondering if I can 'separate' the model part and the input data testing to improve performance as it takes about 3 mins now.
What I would like to do is similar to traditional R modeling where I make the model and run it. Then with the input data, I just call it against the model and the result is calculated in a minimal time. Is there a way to store this already run Forest Model for a quick run later?
Thanks,
Solved! Go to Solution.
Absopositively! When you build the model, you can output the model to a yxdb file. Now you've got a static model. When it comes to scoring within the next workflow, you can input the model object (yxdb) and proceed to score the data without reconstructing the model.
Cheers,
Mark