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Tantrum, J., Murua, A. and Stuetzle, W. (2003) Assessment and Pruning of Hierarchical Model Based Clustering. Proceedings of the 9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 197-205.
http://dx.doi.org/10.1145/956750.956775

has been cited by the following article:

• TITLE: Parallel and Hierarchical Mode Association Clustering with an R Package Modalclust

  AUTHORS: Yansong Cheng, Surajit Ray

  KEYWORDS: Modality, Kernel Density Estimate, Mode, Clustering

  JOURNAL NAME: Open Journal of Statistics, Vol.4 No.10, November 18, 2014

  ABSTRACT: Modalclust is an R package which performs Hierarchical Mode Association Clustering (HMAC) along with its parallel implementation over several processors. Modal clustering techniques are especially designed to efficiently extract clusters in high dimensions with arbitrary density shapes. Further, clustering is performed over several resolutions and the results are summarized as a hierarchical tree, thus providing a model based multi resolution cluster analysis. Finally we implement a novel parallel implementation of HMAC which performs the clustering job over several processors thereby dramatically increasing the speed of clustering procedure especially for large data sets. This package also provides a number of functions for visualizing clusters in high dimensions, which can also be used with other clustering softwares.