data science and machine learning ( r-studio)

need help with lab #4 and 6. please use r-studio and provide me the code with the answer so i can learn from it. thank you.

edit:thats all the question is about. what else do you need? the usual way i do it is to install the package, import library(ISLR) and then work on the problem.

whether customer proceeds to P urchase the insurance depending on 85 variables. (a) What trees are appropriate for this problem - regression or classification? Why? (b) Split the data set half and half into a training set and a test set, respectively. Use the following code (after having loaded the required packages): set.seed(1) train

6. This problem involves the Hitters data set (a part of the ISLR package) on salaries of baseball hitters. (a) Dispose of NA observations and perform log-transformation on Salary variable. Then create a training set containing a random sample of 200 observations. library(ISLR) Hitters$LogSalary 4. We will apply tree-based models for Caravan insurance data. We will seek to predict whether customer proceeds to Purchase the insurance depending on 85 variables. (a) What trees are appropriate for this problem regression or classification? Why? (b) Split the data set half and half into a training set and a test set, respectively. Use the following code (after having loaded the required packages): set.seed(1) train