bias variance decomposition for classification problem

Question

bias variance decomposition for classification problem

IamTheRealFord

2022年5月13日 10:03

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.

Topic bias mathematics variance classification

Category Data Science

ombk · Accepted Answer · 2020年11月24日 00:23

Bias and Variance in Classification problems

Check this link about Support Vector Machine.

You will directly understand bias and variance in classification. Basically, if your data is linearly separable you do not have a problem.

But imagine that your data is pseudo/semi linearly separable, however, few points land on the other side of their group.

Now imagine having a model that separates the data linearly, vs a model that will oscillate through the data so much to be able to classify correctly every point.

Additional link

Eugen · Accepted Answer · 2019年6月25日 11:04

1

Eugen answered at 2019年6月25日 11:04

My opinion is that the bias variance trade off is rooted in the Uncertainty principle. It behaves absolutely the same.

bias variance decomposition for classification problem

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