I am running different algorithms (random forests and logistic regression with Laplace/lasso regularization) for a binary classification problem to compare them thereafter.
I have built the LR algorithm (middle section of the attached workflow) after 10-fold cross-validation and I have two questions:
- How do I get a single AUC derived from the combined effect of all (non-excluded) predictors, instead of one AUC for each predictor?
- How can I get access to variables remaining in the final model after Laplace/LASSO regularization?
Example LR.knwf (68.0 KB)