图 书 馆
用很少的资源训练大的随机森林Training Big Random Forests with Little Resources |
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| 课程网址: | http://videolectures.net/kdd2018_gieseke_training_forests/ |
| 主讲教师: | Fabian Gieseke |
| 开课单位: | 多特蒙德大学计算机科学系 |
| 开课时间: | 2018-11-23 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Without access to large compute clusters, building random forests on large datasets is still a challenging problem. This is, in particular, the case if fully-grown trees are desired. We propose a simple yet effective framework that allows to efficiently construct ensembles of huge trees for hundreds of millions or even billions of training instances using a cheap desktop computer with commodity hardware. The basic idea is to consider a multi-level construction scheme, which builds top trees for small random subsets of the available data and which subsequently distributes all training instances to the top trees’ leaves for further processing. While being conceptually simple, the overall efficiency crucially depends on the particular implementation of the different phases. The practical merits of our approach are demonstrated using dense datasets with hundreds of millions of training instances. |
| 关 键 词: | 大型计算集群; 构建随机森林; 廉价的台式计算机; 小随机子集构建顶层树 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2023-01-30：cyh |
| 最后编审: | 2023-01-30：cyh |
| 阅读次数: | 21 |