In this context, are bias and variance always related to MSE, or only when the cost function for the statistical learning method is related to MSE?
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2$\begingroup$ In which context? $\endgroup$– kjetil b halvorsen ♦Commented Sep 2, 2016 at 12:03
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$\begingroup$ In the context of machine learning "bias variance tradeoff" question $\endgroup$– user_anonCommented Sep 2, 2016 at 12:11
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1$\begingroup$ Although this question seems to be arising from a confusion, it is possible to answer (+1 to @StudentT below). IMO, it can stay open. $\endgroup$– gung - Reinstate MonicaCommented Sep 2, 2016 at 12:28
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I think you're totally confused. Bias/variance relates how well your model fits relative to overfitting and underfitting. MSE is simply one of the many possible measures we can use to quantify how well a model performs.
High bias can be measured by very high MSE and high variance can be measured by very low MSE.
answered Sep 2, 2016 at 12:21
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2$\begingroup$ Low bias would normally be associated with overfitting. Think about Lasso or ridge regression where bias is induced to avoid overfitting. $\endgroup$ Commented Sep 2, 2016 at 12:35
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$\begingroup$ @RichardHardy I think I've given the wrong orders, edited. $\endgroup$ Commented Sep 2, 2016 at 12:45
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