Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
In the documentation, subsample is a parameter appears in the list of parameters for tree boosters only. Please include subsampling for gblinear booster as well. Subsampling of training instances can be very useful for linear boosters, especially there are a large number of predictors. It probably only need a small modification after the gradients are calculated.
I have tried to set the subsample parameter at different values with a gblinear booster, and I got same results (estimated parameter values and predicted values). So perhaps, subsampling only work with tree boosters in current version of xgboost. If I am mistaken, could anyone please tell me how to implement subsampling of training instances with gblinear booters correctly, thank you very much.
In the documentation, subsample is a parameter appears in the list of parameters for tree boosters only. Please include subsampling for gblinear booster as well. Subsampling of training instances can be very useful for linear boosters, especially there are a large number of predictors. It probably only need a small modification after the gradients are calculated.
I have tried to set the subsample parameter at different values with a gblinear booster, and I got same results (estimated parameter values and predicted values). So perhaps, subsampling only work with tree boosters in current version of xgboost. If I am mistaken, could anyone please tell me how to implement subsampling of training instances with gblinear booters correctly, thank you very much.