d$)(40$ points$)$ Create a class method called train$\_$and$\_$validate$\_$diabetes that gets one int

argument called given$\_$seed. This method reads the diabetes data from scikit$-$learn

library using datasets.load$\_$diabetes method. This method reads the

data into a dataframe, and it processes the data such that it can train a model that uses

linear regression to predict the 'target' label.

It splits the data into train and test $($where test will have $30\%$ of the data. You have to

use method train$\_$test$\_$split from scikit$-$learn to split the data, and set

random$\_$state$=$given$\_$seed$).$ It trains a model on train data using LinearRegression from

scikit$-$learn. After the model is trained, it validates the result by calling calculateRMSE

and calculateMAE $($created at subpoints $b)$ and c$)).$ The method returns a tuple

containing $($RMSEvalue$,$ MAEvalue$).$