Variable selection for cluster analysis is a difficult problem. The difficulty originates not only from the lack of class information but also the fact that high-dimensional data ...
Leonard K. M. Poon, Nevin Lianwen Zhang, Tao Chen,...
Abstract. The problem of clustering data can be formulated as a graph partitioning problem. In this setting, spectral methods for obtaining optimal solutions have received a lot of...
Marcus Weber, Wasinee Rungsarityotin, Alexander Sc...
— This paper introduces a quantitative method for social data analysis, which is based on the use of categorical data clustering. More specifically, we employ categorical data cl...
This paper considers the problem of modeling migraine severity assessments and their dependence on weather and time characteristics. We take on the viewpoint of a patient who is i...
The complexity, approximation and algorithmic issues of several clustering problems are studied. These non-traditional clustering problems arise from recent studies in microarray ...