Support Vector Machines

This assignment will build off of the previous ungraded assignment. However, here you will use a radial basis function for your kernel rather than a linear specification.

To begin, a synthetic data set has been provided below. It is normally distributed with an added offset to create two separate classes.

library$($tidymodels$)$

library$($ISLR$2)$

$$

set.seed$(1)$

sim$\_$data$2<-$ tibble$($

x$1=$ rnorm$(200)+$ rep$($c$(2,-2,0),$ c$(100,50,50)),$

x$2=$ rnorm$(200)+$ rep$($c$(2,-2,0),$ c$(100,50,50)),$

y $=$ factor$($rep$($c$(1,2),$ c$(150,50)))$

$)$

$$

sim$\_$data$2\%>\%$

ggplot$($aes$($x$1,$ x$2,$ color $=$ y$))+$

geom$\_$point$()$