All Models of Learning have Flaws by John Langford.
From the post:
Attempts to abstract and study machine learning are within some given framework or mathematical model. It turns out that all of these models are significantly flawed for the purpose of studying machine learning. I’ve created a table (below) outlining the major flaws in some common models of machine learning.
Quite dated (2007) but still quite handy chart of what is “right” and “wrong” about machine learning models.
Would be even more useful with smallish data sets that illustrate what is “right” and “wrong” about each model.
Anything you would add or take away?
I first saw this in a tweet by Computer Science.