XGBoost Distributed Training and Parallel Predictions with Apache Spark
Background In Boosting (ML ensemble method), algorithms implement a sequential process (as opposed to Bagging where it is parallelised) that generates weak learners and combine them to a strong learner (as in all Ensemble methods). In Boosting, at each iteration of this process, the model tries to correct the mistakes of the previous one in […]