LightGBM

LightGBM is a gradient boosting framework that was developed by Microsoft that uses the tree-based learning algorithm in a different fashion than other GBMs, favoring exploration of more promising leaves (leaf-wise) instead of developing level-wise.

In graph terminology, LightGBM is pursuing a depth-first search strategy than a breadth-first search one.

It has been designed to be distributed (Parallel and GPU learning supported), and its unique approach really achieves faster training speed with lower memory usage (thus allowing for the handling of the larger scale of data):

The installation of XGBoost requires some more actions on your side than ...

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