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I was curious to see whether or not there was a common algorithm for mapping two unrelated data sets.

So for example let's say I wanted to give you a spirit animal based on your name, birthday, zodiac sign, height, and weight. How would someone go about creating an algorithm based on that?

Another example is something based on a book you like I will match to you something you should eat for dinner.

How would someone go about this? Would it just be completely biased or is there an algorithm that's based on this? The closest thing I can think of is some kind of recommendation algorithm but I'm not sure.

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  • $\begingroup$ This doesn't sound like a matter of computer science to me. Any community votes? If you know how you want to make a match, we can help you devise algorithms and systems to do that. But we can't tell you how to select a spirit animal for you (just like it's not a matter of computer science to determine who you should date or marry). To put it another way, first you need to be able to specify precisely what you want; then we can tell you how to accomplish that. $\endgroup$
    – D.W.
    May 16, 2022 at 19:01
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    $\begingroup$ A random generator will do marvels. $\endgroup$
    – user16034
    Jun 16, 2022 at 14:48

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For discrete, non numerical data, you can use a relation (in the sense of relational database).

For numerical data, you can use multivariate interpolators, such as neural nets with overfitting.

What you feed to the input of such devices will return as output what was trained on.


Needless to say, if your hope is that you will get interesting outputs from new, unknown inputs, you will be very disappointed.

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