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Taking the regression model as an example, it is recommended to add a parameter "task" when instantiating LightGBMRegressor. I found that I couldn't continue to perform incremental training on the saved models in the form of a string or a file during my use. The LightGBM algorithm in Microsoft includes this part, and I hope to see it gradually supplemented.
predict, for prediction, aliases: prediction, test
convert_model, for converting model file into if-else format, see more information in Convert Parameters
refit, for refitting existing models with new data, aliases: refit_tree
save_binary, load train (and validation) data then save dataset to binary file. Typical usage: save_binary first, then run multiple train tasks in parallel using the saved binary file
The text was updated successfully, but these errors were encountered:
Taking the regression model as an example, it is recommended to add a parameter "task" when instantiating LightGBMRegressor. I found that I couldn't continue to perform incremental training on the saved models in the form of a string or a file during my use. The LightGBM algorithm in Microsoft includes this part, and I hope to see it gradually supplemented.
task 🔗︎, default = train, type = enum, options: train, predict, convert_model, refit, aliases: task_type
train, for training, aliases: training
predict, for prediction, aliases: prediction, test
convert_model, for converting model file into if-else format, see more information in Convert Parameters
refit, for refitting existing models with new data, aliases: refit_tree
save_binary, load train (and validation) data then save dataset to binary file. Typical usage: save_binary first, then run multiple train tasks in parallel using the saved binary file
The text was updated successfully, but these errors were encountered: