Exercise

# Adjusting the regularization strength

Your current Lasso model has an \(R^2\) score of 84.7%. When a model applies overly powerful regularization it can suffer from high bias, hurting its predictive power.

Let's improve the balance between predictive power and model simplicity by tweaking the `alpha`

parameter.

Instructions

**100 XP**

- Find the
**highest**value for`alpha`

that gives an \(R^2\) value above 98% from the options:`1`

,`0.5`

,`0.1`

, and`0.01`

.