Exercise

# High bias or high variance?

In this exercise you'll diagnose whether the regression tree `dt`

you trained in the previous exercise suffers from a bias or a variance problem.

The training set RMSE (`RMSE_train`

) and the CV RMSE (`RMSE_CV`

) achieved by `dt`

are available in your workspace. In addition, we have also loaded a variable called `baseline_RMSE`

which corresponds to the root mean-squared error achieved by the regression-tree trained with the `disp`

feature only (it is the RMSE achieved by the regression tree trained in chapter 1, lesson 3). Here `baseline_RMSE`

serves as the baseline RMSE above which a model is considered to be underfitting and below which the model is considered 'good enough'.

Does `dt`

suffer from a high bias or a high variance problem?

Instructions

**50 XP**

##### Possible Answers

`dt`

suffers from high variance because`RMSE_CV`

is far less than`RMSE_train`

.`dt`

suffers from high bias because`RMSE_CV`

\(\approx\)`RMSE_train`

and both scores are greater than`baseline_RMSE`

.`dt`

is a good fit because`RMSE_CV`

\(\approx\)`RMSE_train`

and both scores are smaller than`baseline_RMSE`

.