wsrf: An R Package for Classification with Scalable Weighted Subspace Random Forests.
文献类型：期刊论文
| 作者 | Zhao, He; Williams, Graham J.; Huang, Joshua Zhexue |
| 刊名 | JOURNAL OF STATISTICAL SOFTWARE
 |
| 出版日期 | 2017 |
| 文献子类 | 期刊论文 |
| 英文摘要 | We describe a parallel implementation in R of the weighted subspace random forest algorithm (Xu, Huang, Williams, Wang, and Ye 2012) available as the wsrfpackage. A novel variable weighting method is used for variable subspace selection in place of the traditional approach of random variable sampling. This new approach is particularly useful in building models for high dimensional data - often consisting of thousands of variables. Parallel computation is used to take advantage of multi-core machines and clusters of machines to build random forest models from high dimensional data in considerably shorter times. A series of experiments presented in this paper demonstrates that wsrf is faster than existing packages whilst retaining and often improving on the classificationperformance, particularly for high dimensional data. |
| URL标识 | 查看原文 |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/12565]  |
| 专题 | 深圳先进技术研究院_数字所 |
| 作者单位 | JOURNAL OF STATISTICAL SOFTWARE |
| 推荐引用方式 GB/T 7714 | Zhao, He,Williams, Graham J.,Huang, Joshua Zhexue. wsrf: An R Package for Classification with Scalable Weighted Subspace Random Forests.[J]. JOURNAL OF STATISTICAL SOFTWARE,2017. |
| APA | Zhao, He,Williams, Graham J.,&Huang, Joshua Zhexue.(2017).wsrf: An R Package for Classification with Scalable Weighted Subspace Random Forests..JOURNAL OF STATISTICAL SOFTWARE. |
| MLA | Zhao, He,et al."wsrf: An R Package for Classification with Scalable Weighted Subspace Random Forests.".JOURNAL OF STATISTICAL SOFTWARE (2017). |
入库方式： OAI收割
来源：深圳先进技术研究院
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