LightGBM Library
A LightGBM Library is an open source ML library that specializes in gradient boosting.
- Example(s):
- lightgbm v2.0.11[1] ~(2017-11-15).
- …
- Counter-Example(s):
- See: Apache Flink.
References
2018
- https://towardsdatascience.com/catboost-vs-light-gbm-vs-xgboost-5f93620723db
- QUOTE: ... LightGBM uses a novel technique of Gradient-based One-Side Sampling (GOSS) to filter out the data instances for finding a split value while XGBoost uses pre-sorted algorithm & Histogram-based algorithm for computing the best split. Here instances means observations/samples. ...
- QUOTE: ... LightGBM uses a novel technique of Gradient-based One-Side Sampling (GOSS) to filter out the data instances for finding a split value while XGBoost uses pre-sorted algorithm & Histogram-based algorithm for computing the best split. Here instances means observations/samples. ...
2017
- https://github.com/Microsoft/LightGBM
- QUOTE: A fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. It is under the umbrella of the DMTK(http://github.com/microsoft/dmtk) project of Microsoft.
LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed and efficient with the following advantages:
- Faster training speed and higher efficiency
- Lower memory usage
- Better accuracy
- Parallel and GPU learning supported
- Capable of handling large-scale data
- QUOTE: A fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. It is under the umbrella of the DMTK(http://github.com/microsoft/dmtk) project of Microsoft.