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Many people use the MSE decomposition to illustrate bias and variance. However, is there any statistical learning theory connecting these concepts? Namely, is there a formula calculating model capacity using bias and variance?

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    $\begingroup$ Qualitatively, models that are richer / more complex have higher variance and lower bias. $\endgroup$
    – angryavian
    Oct 27 '20 at 21:55
  • $\begingroup$ what is model capacity $\endgroup$
    – develarist
    Oct 27 '20 at 23:50
  • $\begingroup$ @angryavian Is there any equation depicting such kind of relationship? $\endgroup$
    – JP Zhang
    Oct 29 '20 at 0:47
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I think this issue is perfectly discussed and explained by Dr. Kilian Weinberger from Cornel University.

Here are the lecture notes: http://www.cs.cornell.edu/courses/cs4780/2018fa/lectures/lecturenote12.html

and http://www.cs.cornell.edu/courses/cs4780/2018fa/lectures/lecturenote11.html

You can also find video recordings of the course, so you can follow up.

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