
Misleading modelling: overfitting, cross-validation, the bias-variance trade-off - stared
http://blog.cambridgecoding.com/2016/03/24/misleading-modelling-overfitting-cross-validation-and-the-bias-variance-trade-off/
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joe_the_user
This is a marvelous articles indicating talking about dangers and trade-offs.

The thing about the diagrams is if the data was points on a coastline, maybe
the most overfit curve would be the most useful. It seems like this kind of
thing doesn't have an absolutely objective answer but depends on context (why
one talks about tradeoffs, not laws).

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rcthompson
Yes, you're correct, the sweet spot between under- and overfitting is
completely dependent on the nature of the data set, and cannot be determined
_a priori_. That's why cross-validation and similar techniques are critical
for determining the right trade off between bias and variance.

