An R code for implementing non-hierarchical algorithm for clustering of probability density functions

Ngoc Diem Tran, Tom Vinant, ThéO Marc Colombani, Kieu Diem Ho
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引用次数: 1

Abstract

This paper aims to present a code for implementation of non-hierarchical algorithm to cluster probability density functions in one dimension for the first time in R environment. The structure of code consists of 2 primary steps: executing the main clustering algorithm and evaluating the clustering quality. The code is validated on one simulated data set and two applications. The numerical results obtained are highly compatible with that on MATLAB software regarding computational time. Notably, the code mainly serves for educational purpose and desires to extend the availability of algorithm in several environments so as having multiple choices for whom interested in clustering.  This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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实现概率密度函数聚类的非分层算法的R代码
本文旨在首次在R环境下实现一维概率密度函数聚类的非分层算法代码。代码结构包括两个主要步骤:执行主聚类算法和评估聚类质量。该代码在一个模拟数据集和两个应用程序上进行了验证。所得到的数值结果在计算时间上与MATLAB软件的结果高度吻合。值得注意的是,该代码主要用于教育目的,并希望扩展算法在多个环境中的可用性,以便为对聚类感兴趣的人提供多种选择。这是一篇在知识共享署名许可(http://creativecommons.org/licenses/by/4.0/)下发布的开放获取文章,该许可允许在任何媒体上不受限制地使用、分发和复制,前提是正确引用原始作品。
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