$(10$ points$)($a$)$ Decide whether the following statement is true or false:

Scaling numerical variables can sometimes improve the error of predictions of linear regression models.

$($b$)$ In this class we have learned about several machine learning algorithms. These include the following: decision trees, bagging,

random forests, nearest neighbor, linear regression, $k-$means clustering, hierarchical clustering.

Of these $7$ algorithms, is any a generalization of any other, or are they all essentially different? Say which of these options is correct,

and if one is a generalization of another give a specific example.