Problem $2($Bias & Variance Trade$-$off, $6$ points$)$ The bias$-$variance tradeoff is a fundamental concept in machine learning that describes the relationship between a model$$s complexity and accuracy. Please determine the TRUE$/$FALSE of the following statements about bias$-$variance tradeoff. In either case, explain your choice$($s$)$ briefly: $($a$)$ Removing some of the non$-$support vectors in SVM has no effect on the bias and variance. $($b$)$ Properly increasing the width of the deep neural network will decrease the bias and variance. $($c$)$ The bias of LDA could be caused by the assumption that the data follow the Gaussian distribution.