Asymmetric biclustering with constrained von Mises-Fisher models

International Meeting on High-Dimensional Data-Driven Science 2015

Watanabe, Kazuho^1 ; Wu, Hsiang-Yun^2 ; Takahashi, Shigeo^3 ; Fujishiro, Issei^2

Department of Computer Science and Engineering, Toyohashi University of Technology, 1-1 Hibarigaoka, Tempaku-cho, Aichi, Toyohashi

441-8580, Japan^1

Department of Information and Computer Science, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Kanagawa, Yokohama

223-8522, Japan^2

Department of Computer Science and Engineering, University of Aizu, Tsuruga, Ikki-machi, Aizu-Wakamatsu, Fukushima

965-8580, Japan^3

关键词: Data analysis methods;    Directional statistics;    Multivariate data visualization;    Parallel coordinate plots;    Probabilistic modeling;    Similarity measure;    Variational Bayesian inferences;    Von Mises-Fisher (vMF) distribution;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/699/1/012018/pdf
DOI  :  10.1088/1742-6596/699/1/012018

来源: IOP

【 摘 要 】

As a probability distribution on the high-dimensional sphere, the von Mises-Fisher (vMF) distribution is widely used for directional statistics and data analysis methods based on correlation. We consider a constrained vMF distribution for block modeling, which provides a probabilistic model of an asymmetric biclustering method that uses correlation as the similarity measure of data features. We derive the variational Bayesian inference algorithm for the mixture of the constrained vMF distributions. It is applied to a multivariate data visualization method implemented with enhanced parallel coordinate plots.