I don't understand why the height and weight errors aren't 0 when they are known inputs? If I say how tall I am, why is the model estimating something else?

from the title, i thought that will be akinator that produce you some images by image-v2

Tangential, but does anyone else keep reading "MLP" as "my little pony".

AI or not, I liked this bit:

> Averages lie about the tails, and a person who gets a 15 cm bust error doesn’t care that the mean is 4 cm.

A variation of that sentence should be mandatory in every scientific paper.

Interesting idea. Using a questionnaire as input for an MLP makes sense but the real challenge is designing questions that capture useful signal instead of noise. If that part is done well, the approach has a lot of potential.

How big are the pockets and is it sex determined?

Well sorry no, because already the torso to leg length ratio is covered by none of their question. (and yes, they list it as a limitation)

I'm guessing the writing is AI-assisted (there's no fluidity and it has some weirdly placed phrases) but I see they're in Poland and likely not English-language first?

It has that kind of feel as if it's made in codex.

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ai;dr

MLP trained on 8 questions achieves ~0.3cm height error, ~0.3kg weight error, and ~3-4cm for bust/waist/hips measurements.

https://www.mdpi.com/1424-8220/22/5/1885 + some hacking => "we want to productize this"

It takes more like 10 seconds. For a large range of height and weight inputs crossed with all option combinations, you could precompute ~10M measurements and return results basically instantly.

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This is the best UI/UX article I've read this year. If the authors are around, I extend them my dearest congratulations ^^.