For R , , partition the data sets into 6 0 % 6 0 % training and 4 0 % 4 0 % validation and

For R$,$ partition the data sets into $60\%$ training and $40\%$ validation and implement the $10-$fold cross$-$validation. Use the statement set.seed$(1)$ to specify the random seed for data partitioning and cross$-$validation. When searching for the optimal value of k$,$ search within possible k values from $1$ to $10.$ If the predictor variable values are in the character format, then treat the predictor variable as a categorical variable. Otherwise, treat the predictor variable as a numerical variable.

The accompanying data file contains $60$ observations with the binary target variable y along with the predictor variables x$1$ and x$2.$

Click here for the Excel Data File

a$.$ Perform KNN analysis. What is the optimal value of k$?$