When training a linear SVM model , the C meta-parameter weights the cost of classification errors (versus the margin). What happens if you increase the value of C meta-parameter?

Question

When training a  linear SVM model , the C meta-parameter weights the cost of classification errors (versus the margin). What happens if you  increase the value of C  meta-parameter?

Accepted Answer

It increases the variance of the model, increases its sensitivity to noise, and leads to smaller margins.

Answer

It increases the bias of the model, reduces it sensitivity to noise, and leads to larger margins.

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When training a linear SVM model , the C meta-parameter weights the cost of cla...

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