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DreamMidnight t1_jchxtfy wrote

Reply to comment by LeN3rd in [D] Simple Questions Thread by AutoModerator

Yes, although I am specifically looking into the reasoning of "at least 10 datapoints per variable."

What is the mathematical reasoning of this minimum?

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LeN3rd t1_jcislrk wrote

I have not heard this before. Where is it from? I know that you should have more datapoints than parameters in classical models.

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DreamMidnight t1_jcrh53z wrote

Here are some sources:

https://home.csulb.edu/~msaintg/ppa696/696regmx.htm

https://developers.google.com/machine-learning/data-prep/construct/collect/data-size-quality (order of magnitude in this case means 10)

https://stats.stackexchange.com/questions/163055/clarification-on-the-rule-of-10-for-logistic-regression

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LeN3rd t1_jct6arv wrote

Ok, so all of these are linear ( logistics) regression models, for which it makes sense to have more data points, because the weights aren't as constraint as in a convolutional layer I.e. but it is still a rule of thumb, not exactly a proof.

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VS2ute t1_jd1irhb wrote

If you have random noise on a variable, it can have a substantial effect when too few samples.

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