Is the combination of labeled and unlabeled data the way to deploy prediction models?

Is the combination of labeled and unlabeled data onlt way to deploy prediction models generated by auto model in RapidMiner Studio?

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sgenzer

hello @virpi_hotti welcome to the community. I think I just talked to a colleague of yours today on chat?

So what you describe IS basically the definition of predictive analytics. That's the way it's done. Maybe you can explain a bit more what you're doing? Or maybe I did not not understand your question?

Scott

virpi_hotti

For example, there are two samples Titanic Training and Titanic Unlabeled - I combined them in Excel and then I import one file and generate parsimonious models for predictions. If you have a better ideas to deploy and compare the parsimonious models - please, let me know.

IngoRM

Hi,

No, but it is probably the easiest way to deploy a model (although not the best or most time-efficient). There are probably a dozen or so ways to deploy models in RapidMiner. I recommend a visit in our Academy at http://academy.rapidminer.com to learn more about them.

Here are a couple of pointers:

There is in fact a whole part of the catalog dealing with model deployment: https://academy.rapidminer.com/catalog?labels=["Phase"]&values=["Deployment"]

Hope this helps,

Ingo