The growclusters package for R implements an enhanced version of k-means clustering that allows discovery of local clusterings or partitions for a collection of data sets that each draw their cluster means from a single, global partition. The package contains functions to estimate a partition structure for multivariate data. Estimation is performed under a penalized optimization derived from Bayesian non-parametric formulations. This paper describes some of the functions and capabilities of the growclusters package, including the creation of R Shiny applications designed to visually illustrate the operation and functionality of the growclusters package.
翻译:growclusters包是基于R编程语言实现的新型k均值聚类算法。该算法可发现本地聚类或多数据集之间的全局聚类平均值,适用于多元数据的聚类分析。使用贝叶斯非参数模型推理的惩罚优化方法来估计分区结构。本文介绍了growclusters包的功能和特点,并介绍了使用R Shiny应用程序设计展示growclusters包操作和功能的方法。