[Feature Request]: Classification Learner for `ml_l`

### Describe the feature you want to propose or implement

Currently, `ml_m` allows for a classfication learner while `ml_l` does not. What is the rationale behind this choice? It could easily be the case that both the treatment `D` and the outcome `Y` are binary variables in which case it is desirable to use classification learners on both stages.

### Propose a possible solution or implementation

_No response_

### Did you consider alternatives to the proposed solution. If yes, please describe

_No response_

### Comments, context or references

_No response_

Start by comparing the existing classification-learner support in `ml_m` with the implementation and learner validation for `ml_l`. Determine the intended behavior for binary treatment and outcome variables, then add the corresponding support and tests so classification learners work consistently in both stages.

Written by the indexing model from the issue text.