# bias variance decomposition for classification problem

It is given that:

MSE = bias$$^2$$ + variance

I can see the mathematical relationship between MSE, bias, and variance. However, how do we understand the mathematical intuition of bias and variance for classification problems (we can't have MSE for classification tasks)?

I would like some help with the intuition and in understanding the mathematical basis for bias and variance for classification problems.

Any formula or derivation would be helpful.

• I don't fully understand the question, what are you looking for exactly? Jun 19, 2019 at 13:32
• oops sorry. Updated in the question itself. What to know mathematical intuition of bias variance for classification problem. Fore regression it has relation with MSE but classification how to relate them.? Jun 21, 2019 at 8:51
• WHAT classification? Logit? Jun 21, 2019 at 20:01
• If you are looking for the concept, see datascience.stackexchange.com/questions/53758/… and deeplearningbook. Jun 25, 2019 at 6:43
• ya already gone through that. But how will it work for classification problem.? (we dont have mse there know) Jun 25, 2019 at 7:17

Bias and Variance in Classification problems 