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Sir-Rhino t1_j1a3o4a wrote

I don't know much about models for tabular data.

That being said, it sounds like you want to pick/select a certain member/item from a group of 50? Instead of predicting the corresponding value, maybe you could just predict the index of that item.

Don't have much more to add. If you provide a bit more context about what you're trying to achieve someone may be able to provide more feedback. BTW this type of post is probably more suited for /r/learnmachinelearning , so try there too.

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blablanonymous t1_j1a5ovy wrote

Maybe give an example? Maybe I’m just slow but I think it’s ambiguous the way it’s phrased

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rapp17 OP t1_j1a9akp wrote

I have a quantity of 100 units that need to be allocated across 50 days. The data set is comprised of hundreds of these scenarios X quantity allocated across 50 days. The quantity varies but number of days remain the same. What's the best way to get an ML model to do this.

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blablanonymous t1_j1aacs3 wrote

It sounds more like constrained optimization than ML but still too vague of an explanation for me to be helpful so I’m giving up. Good luck

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flapflip9 t1_j1dk0ke wrote

Sounds like you want to predict 50 values, given 150 inputs. ML might work, but I doubt you'd have enough data to avoid over fitting.

It also sounds like it's not like there's a single correct numerical answer for any given day, rather, you're trying to find a decent distribution. So look first into constrained optimizations first, similar to budget allocation or task distribution optimizations.

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