Question $3$ Programming supervised learning

In this question, you use an OpenML dataset of diabetes with ID $42363,$ https:$//$www$.$openml.org$/$search$?$type$=$data&status$=$active&id$=42363.$ The dataset can be loaded using the following code:

from sklearn.datasets import fetch$\_$openml dataset $=$ fetch$\_$openml$($data$\_$id$=42363)$

$($a$)$ Write code to load and explore the dataset by printing its feature data$$s shape, target$$s shape, feature names, target names, and textual description. $[4]$

$($b$)$ Write code to create a pandas DataFrame from the dataset, and display the DataFrame and the DataFrame$$s descriptive statistics. $($Hint: use the display$()$ function for better formatted output.$)[4]$

$($c$)$ Write code to train a linear regression model for the dataset. Use only the last $4$ features in the dataset, i$.$e$.$temp$,$RH$,$wind$$ and $$rain$.$ Split the dataset into a training set and a test set, and do not use cross$-$validation. Display the test score of the model. $[5]$

$($d$)$ Write code to train a linear regression model for the dataset using $10-$fold cross$-$ validation. Use only the last $4$ features in the dataset, i$.$e$.$temp$,$RH$,$wind$$ and $$rain$.$ Use $$neg$\_$mean$\_$absolute$\_$error$$ for scoring in CV$.$ Display the mean score. $[5]$

$($e$)$ Write code to train a SVR model for the dataset using $10-$fold cross$-$validation. Use only the last $4$ features in the dataset, i$.$e$.$temp$,$RH$,$wind$$ and $$rain$.$ Use $$neg$\_$mean$\_$absolute$\_$error$$ for scoring in CV$.$ Display the mean score. $[5]$

$($f$)$ State the scores of the models in parts $($d$)$ and $($e$),$ and comment on which of the two models performs better. $[2]$