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In recent versions of the LightGBM model, a new feature called linear trees has been introduced: link to the feature.
However, if I convert a linear tree model to the DAAL format, it can only store the leaf constant value, not the linear model within the leaf node.
Could this feature be added? I would greatly appreciate it.
The text was updated successfully, but these errors were encountered:
According to your request, is it possible to use C++ interfaces to 1) convert trained LGBM models to oneDAL and 2) predict with converted oneDAL models?
According to your request, is it possible to use C++ interfaces to 1) convert trained LGBM models to oneDAL and 2) predict with converted oneDAL models?
I have only tried converting LightGBM models to the Python version of oneDAL for inference. Since it does not support linear models, I did not explore further. Therefore, I am not sure how to use the C++ interface with oneDAL models converted from LGBM.
Subsequently, I implemented my own CUDA-accelerated inference process for LightGBM with linear_tree=true.
I noticed that the leaf nodes in decision trees only contain a single response value, as seen in this example:
oneDAL/cpp/daal/include/algorithms/tree_utils/tree_utils_regression.h
Line 51 in bbe13a4
oneDAL/examples/daal/cpp/source/gradient_boosted_trees/gbt_reg_traversed_model_builder.cpp
Line 92 in bbe13a4
In recent versions of the LightGBM model, a new feature called linear trees has been introduced: link to the feature.
However, if I convert a linear tree model to the DAAL format, it can only store the leaf constant value, not the linear model within the leaf node.
Could this feature be added? I would greatly appreciate it.
The text was updated successfully, but these errors were encountered: