I finished the course 1 but one question that didn’t find the answer for was how do I choose the right variable for linear regression. i.e how do I measure the effectivness of linear regression ( for example does the model predict values at 90% accuracy etc). I may have missed it. Can anyone guide me?

For **linear** regression, use metrics like `mean squared error`

or `mean absolute error`

on the test set to get a picture of how well your model generalizes to unseen data.

Accuracy is a metric applicable to **logistic** regression but the same idea holds true. Measure model performance on the test set.