I'm excited to see #gradientboosting making some news! There is so much #aihype around #llms (and before that it was #deeplearning) but I think that for most #datascientists working in industry the development of #gradientboosting #machinelearning algorithms (like #xgboost and #catboost) are the real revolution and will have a much more long lived impact on our work.

https://www.nature.com/articles/s41598-022-20149-z

Using the #ensemble of #gradientboosting regression models for FedCSIS 2022 Challenge: “Diversified gradient boosting ensembles for prediction of the cost of forwarding contracts” by D. Ruta, M. Liu, L. Cen, QH Vu. @FedCSIS
2022, ACSIS Vol. 30 p. 431–436; http://tinyurl.com/4vszh6wt

#MachineLearning lesson of the day: Working with a #gradientboosting model, I got no traction cross-validating hyperparameters like tree depth and number; but different evaluation metrics (e.g. SMSE vs. MAE etc.) had a major impact. Have you tried this?

IMHO #DNN get all the press because they do sexy human jobs like seeing and processing language. But in the business world of tabular data, #gradientboosting is where the real revolution is happening! #xgboost #catboost #lightgbm #DataScience