In SVMs$,$ a large functional margin represents a confident and correct prediction. Let the functional margins be defined as :

y$^($i$)=$y$($i$)($wTx$+$b$)$

and the linear classifier as hw$,$b$($x$)=$g$($wTx$+$b$)$

For any choice of suitable g$(),$ if we replace w by $2$w and b by $2$b$,$ which of the following is likely to be observed?

No change in hw$,$b$($x$)=$g$($wTx$+$b$)$

$.$

Will result in reducing the functional margin by half.

Change in geometric margin.

None of the above.