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To boost LSS models the following things needs to be done:
the base-learner track should be able to get initialized with a multidimensional response, then a hash map is created with vectors for each response
The optimizer needs to loop over the map (controlled from compboost.cpp)
The loop (in compboost.cpp) should update the response directly, then the next "response model" could use the updated response (corresponds to cyclic updates)
Think about how estimated parameter are returned, how selected base-learners are returned (maybe as matrix) and so on
Think about how stopping criteria comes in here
We need special loses for that structure, the loss should control how the response looks like (maybe)
Each response should get an optimizer (just to provide modularity)
The text was updated successfully, but these errors were encountered:
To boost LSS models the following things needs to be done:
The text was updated successfully, but these errors were encountered: