Global refinement of random forest

IEEE Conference on Computer Vision and Pattern Recognition, pp. 723-730, 2015.

被引用78|引用|浏览144|来源
EI WOS

摘要

Random forest is well known as one of the best learning methods. In spite of its great success, it also has certain drawbacks: the heuristic learning rule does not effectively minimize the global training loss; the model size is usually too large for many real applications. To address the issues, we propose two techniques, global refineme...更多

代码

数据

您的评分 :
0

 

标签
评论