The dataset ToyotaCorolla.csv contains data on used cars on sale during the late summer of 2004 in the Netherlands. It has 1436 records containing details on 38 attributes, including Price, Age, Kilometers, HP, and other specifications. We plan to analyze the data using various data mining techniques. Write the R code for the following:

a) Randomly partition the dataset(use seed = 1): Partitioning percentages for training (70%), validation (30%).

b) Remove ID variable from the dataset.

c) Run a linear regression model using training data to predict the price of the car, using rest of the variables. If needed, appropriately change variables class to factor before running regression. e) Use the above model to predict the prices of cars in the test data and report accuracy