[SYSTEMDS-1938] Regularized Greedy Forest (RGF) Implementation

• Type: New Feature
• Status: Open
• Priority: Minor
• Resolution: Unresolved
• Component/s: Algorithms
• Assignee: Unassigned
• Reporter: Janardhan Pulivarthi
• Created: 26/Sep/17 13:44
• Updated: 26/Sep/17 13:53

Description

RGF is a machine learning method for building decision forests. Based on
1. Learning Nonlinear Functions UsingRegularized Greedy Forest - https://arxiv.org/pdf/1109.0887.pdf
2. Robust LogitBoost and Adaptive Base Class (ABC) LogitBoost - https://arxiv.org/ftp/arxiv/papers/1203/1203.3491.pdf
3. A general boosting method and its application to learning ranking functions for web search - https://papers.nips.cc/paper/3305-a-general-boosting-method-and-its-application-to-learning-ranking-functions-for-web-search.pdf

A C++ implementation is at https://github.com/baidu/fast_rgf

Issue Links

• contains: SYSTEMDS-822 Gradient Boosted Trees