R/DWD：用于分类、可视化和批量调整的距离加权判别。
R/DWD: distance-weighted discrimination for classification, visualization and batch adjustment.
机构信息
Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
出版信息
Bioinformatics. 2012 Apr 15;28(8):1182-3. doi: 10.1093/bioinformatics/bts096. Epub 2012 Feb 24.
UNLABELLED
R/DWD is an extensible package for classification. It is built based on a recently developed powerful classification method called distance weighted discrimination (DWD). DWD is related to, and has been shown to be superior to, the support vector machine in situations that are fundamental to bioinformatics, such as very high dimensional data. DWD has proven to be very useful for several fundamental bioinformatics tasks, including classification, data visualization and removal of biases, such as batch effects. Earlier DWD implementations, however, relied on Matlab, which is not free and requires a license. The major contribution of the R/DWD package is an implementation that is completely in R and thus can be used without any requirements for licensing or software purchase. In addition, R/DWD also provides efficient solvers for second-order-cone-programming and quadratic programming.
AVAILABILITY AND IMPLEMENTATION
The package is freely available from cran.r-project.org.
未加标签
R/DWD 是一个可扩展的分类软件包。它是基于一种新开发的强大分类方法，称为距离加权判别（DWD）构建的。DWD 与支持向量机（SVM）有关，并且在生物信息学中非常重要的情况下表现优于 SVM，例如在高维数据的情况下。DWD 已被证明对包括分类、数据可视化和消除偏差（如批次效应）在内的多个基本生物信息学任务非常有用。然而，早期的 DWD 实现依赖于 Matlab，Matlab 不是免费的，需要许可证。R/DWD 软件包的主要贡献是完全用 R 实现的，因此无需任何许可或软件购买要求即可使用。此外，R/DWD 还为二阶锥规划和二次规划提供了有效的求解器。
可用性和实现
该软件包可从 cran.r-project.org 免费获得。
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