Ex-3: There is a Car manufacturer company that has manufactured a new SUV car. The company wants to give the ads to the users who are interested in buying that SUV. So for this problem, we have a dataset that contains multiple user's information through the social network. The dataset contains lots of information but the Estimated Salary and Age we will consider for the independent variable and the Purchased variable is for the dependent variable. Below is the dataset: Represent the gender as Male =1 and Female =2 to map the attribute in R space. - We would like to know which K is the best to classify user's purchased status (1 = buying the car, O= not buying the car). Where K ranges between 1,3 , and 5 . Following the validation-set method to determine that and consider the first and last three instances of the dataset are your validation set (i.e., in total 6 instances) and the rest is your training dataset. To calculate the test-error, follow a simple accuracy measure where: Accurcy=totalnumberofinstancesinthesetnumberoferrors(f(x)=f(x))