hi team - It is unclear how DR approaches datasets where multicollinearity is presented. Can you share more details? Also what tools and capabilities are available to help the users to remove multicollinearity in the data? Thank you!
If you want to go further, you can also go to a given model and then go to Advance setting under Evaluation and set L1 and L2 regularization.
For instance, for an XGboost under Advance setting you have reg_alpha and reg_beta (L1, L2, respectively). You can provide multiple values and let DataRobot find the best one to reducing or removing the influence of redundant features
Links to the documentations about creating feature lists and feature associations.