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I'm working with VIN's and trying to predict purchase prices. In setting up the assisted modeling tool, I have too many makes and models to use as predictors. Anyone use a batch macro to break up the data into something more "normalized" for the tool to analyze?
Thanks for the response ArtApa. That's above my predictive knowledge set as I'm very new to this. Really what I'm trying to do it get the Assisted Modeling tool to accept additional fields as features for the analysis. There are so many makes, models, and trim packages of vehicles that the tool won't accept them. I've tried feeding in only the most common makes and models but the trims make the data fields grow exponentially. I thought if i feed each make and model in separately through a batch macro, then it would accept all three of those fields as features. Thoughts?
just a quick update in case anyone else encounters this...it works. There are additional considerations that I've had to account for...such as replacing missing values before creating the model or ensuring there is a missing value for everything. However, I've found this a great work around for a large data set when you have many different features but you can use one of your features to create "batches" to send through the model in groups at a time.