Discussion of 'Model-based clustering and classification with non-normal mixture distributions' by S.X. Lee and G.J. McLachlan

Giuliano Galimberti; Angela Montanari

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Discussion of 'Model-based clustering and classification with non-normal mixture distributions' by S.X. Lee and G.J. McLachlan

机译：S.X对“基于模型的具有非正态混合分布的聚类和分类”的讨论。李和G.J.麦克拉克伦

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It is a great pleasure to have the chance of reading and commenting on this very interesting paper that provides a unified view on non-gaussian mixture models. It is a very hot topic that has recently been receiving increasing attention in the literature. This paper is especially welcome as it offers to the reader an up-to-date review, with interesting stimuli for reflection and further insight. We would like to comment on the clustering side of the work. The many examples discussed in the paper show how the choice of the distributional shape for the mixture components can affect the clustering performances of the corresponding mixture model. The clustering results are assessed by comparison with a priori known information about group membership through the Adjusted Rand Index (ARI) or the misclassification rate.

机译：很高兴有机会阅读和评论这篇非常有趣的论文，该论文提供了非高斯混合模型的统一视图。这是一个非常热门的话题，最近在文献中受到越来越多的关注。本文特别受欢迎，因为它为读者提供了最新的评论，并提供了有趣的刺激以供反思和进一步了解。我们想在工作的集群方面发表评论。本文讨论的许多示例表明，混合物成分的分布形状的选择如何影响相应混合物模型的聚类性能。通过与经过调整的兰德指数（ARI）或分类错误率的有关组成员资格的先验信息进行比较，评估聚类结果。

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来源
《Statistical Methods and Applications》 |2013年第4期|463-465|共3页
作者
Giuliano Galimberti; Angela Montanari;
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作者单位

Department of Statistical Sciences, University of Bologna, Via delle Belle Arti, 41, 40126 Bologna, Italy;

Department of Statistical Sciences, University of Bologna, Via delle Belle Arti, 41, 40126 Bologna, Italy;

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1. Discussion of “Model-based clustering and classification with non-normal mixture distributions” by S.X. Lee and G.J. McLachlan [J] . Giuliano Galimberti, Angela Montanari Statistical Methods & Applications . 2013,第4期

机译：S.X讨论了“基于模型的具有非正态混合分布的聚类和分类”。李和G.J.麦克拉克伦
2. Discussion of ‘Model-based clustering and classification with non-normal mixture distributions’ by Lee and McLachlan [J] . Paul D. McNicholas, Ryan P. Browne, Paula M. Murray Statistical Methods & Applications . 2013,第4期

机译：Lee和McLachlan讨论了“具有非正态混合分布的基于模型的聚类和分类”
3. Discussion of 'Model-based clustering and classification with non-normal mixture distributions' by Lee and McLachlan [J] . Paul D. McNicholas, Ryan P. Browne, Paula M. Murray Statistical Methods and Applications . 2013,第4期

机译：Lee和McLachlan讨论了“基于模型的具有非正态混合分布的聚类和分类”
4. Generative model-based speaker clustering via mixture of von Mises-Fisher distributions [C] . Hao Tang, Chu S.M., Huang T.S. IEEE International Conference on Acoustics, Speech and Signal Processing;ICASSP 2009 . 2009

机译：通过混合von Mises-Fisher分布来生成基于模型的说话人聚类
5. Latent Multi-State Models for Non-Equidistant Longitudinal Observations with Finite and Infinite Mixture Model-Based Clustering [D] . Luo, Yu. 2019

机译：具有有限和无限混合模型的聚类非等距纵向观测的潜在多状态模型
6. Model-based clustering of DNA methylation array data: a recursive-partitioning algorithm for high-dimensional data arising as a mixture of beta distributions [O] . E Andres Houseman, Brock C Christensen, Ru-Fang Yeh, 2008

机译：DNA甲基化阵列数据的基于模型的聚类：针对β分布混合出现的高维数据的递归划分算法
7. Mixtures of Generalized Hyperbolic Distributions and Mixtures of Skew-t Distributions for Model-Based Clustering with Incomplete Data [O] . Wei, Yuhong, Tang, Yang, McNicholas, Paul D. 2017

机译：广义双曲分布的混合和skew-t的混合基于模型的不完全数据聚类分布

Discussion of 'Model-based clustering and classification with non-normal mixture distributions' by S.X. Lee and G.J. McLachlan

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