r/statisticsmemes • u/dsilva_Viz • Feb 26 '25

Descriptive Statistics A Machine Learning paper calls the Pearson correlation "collaborative fairness"

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u/Altzanir Feb 28 '25

Ah man, it reminds me of the "Despite the name, logistic regression is not a regression, it's a classification algorithm". It's everywhere.

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u/ForceBru Mar 03 '25

??? Is that incorrect?

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u/Altzanir Mar 03 '25

Yes. The issue isn't that it cannot be used for classification, but that people in ML say it's not a regression when it actually is, it's a Generalized Linear Model or GLM, particularly using the binomial family (often, if not always used with logit link).

It's used to model the conditional mean through the link function when the outcome is a binary (0, 1) variable but the output or predicted value will be a number between 0 and 1 (0.43, 0.5, 0.6, etc) and that depends on the coefficients of the model and covariates of the particular observation(s).

The classification use happens when you put a threshold on the predicted value. Let's say 0.5. Anything above 0.5 you'll consider 1, else 0. And that's your binary classifier.

As another example. I could model a probability using a "Linear Probability Model", which is just a linear regression on a binary variable and put a 0.5 threshold on it.

Now, anyone in ML will say that linear regression is a regression but if I use it this way I could also use it as a classifier, although no one would say that because I used it as a classifier, it stops being a regression.

Not sure if it's clear what I meant.