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nins_ t1_iu5na8f wrote

Is the input space very large?

What if you train a model to predict the actual value using your dataset and then simply run an exhaustive prediction over your input space? Then lookup the closest model output value whenever you need it and check the corresponding input parameters.

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ARFGHA OP t1_iu8035e wrote

The input space is in the order of millions, so I think that is still a valid approach.

I was actually thinking about doing the same but I'm not sure how accurate the results of such model would be. I think the accuracy here will be limited with the granularity of the input space.

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seanv507 t1_iu5yc5p wrote

Bayesian optimisation

Response surface methodology

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ARFGHA OP t1_iu80f05 wrote

Thanks I will take a look at the response surface methodology since I'm not really familiar with

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pangolin_fly t1_iu55zhp wrote

Can't really help you with how you would achieve this using machine learning; But I can recommend you take a look at surface fitting techniques such as gaussian process regression? They're the tools I would likely reach for when addressing such problem

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ARFGHA OP t1_iu80gko wrote

Thanks for the suggestion. I will take a look.

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r_linux_mod_isahoe t1_iu5xoua wrote

sorry, we don't answer homework questions here

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ARFGHA OP t1_iu7znga wrote

It is actually not a homework. I'm taking part in a new project that I never worked on before and I justed wanted to brainstorm here with the community since I don't know where to start. I'm not asking for a particular solution but rather looking for direction in terms methods from experienced people.

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