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tgboost - Tiny Gradient Boosting Tree

  •    Java

It is a Tiny implement of Gradient Boosting tree, based on XGBoost's scoring function and SLIQ's efficient tree building algorithm. TGBoost build the tree in a level-wise way as in SLIQ (by constructing Attribute list and Class list). Currently, TGBoost support parallel learning on single machine, the speed and memory consumption are comparable to XGBoost. Handle missing value, XGBoost learn a direction for those with missing value, the direction is left or right. TGBoost take a different approach: it enumerate missing value go to left child, right child and missing value child, then choose the best one. So TGBoost use Ternary Tree.

fast_retraining - Show how to perform fast retraining with LightGBM in different business cases

  •    Jupyter

In this repo we compare two of the fastest boosted decision tree libraries: XGBoost and LightGBM. We will evaluate them across datasets of several domains and different sizes.On July 25, 2017, we published a blog post evaluating both libraries and discussing the benchmark results. The post is Lessons Learned From Benchmarking Fast Machine Learning Algorithms.