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Generalization is standard lingo in machine learning – it's about going from known data (training set / test set) to new data which shares the same underlying patterns but wasn't available at learning time.

Taking the posts simple polynomial example, it would be going from

4x^2 + 2x -3 = 0

to

2x^2 -5x +2 = 0

or more generally to

ax^2 + bx + c = 0

The intended audience is people who are knowledgeable about spaced repetition, and such people typically know what generalization means in the context of learning.

I mean, just the standard dictionary meaning of generalization works just fine here, no? I had no problems following the article.