—In this paper, we have modified a constrained clustering algorithm to perform exploratory analysis on gene expression data using prior knowledge presented in the form of constr...
Erliang Zeng, Chengyong Yang, Tao Li, Giri Narasim...
Detection of space-time clusters is an important function in various domains (e.g., epidemiology and public health). The pioneering work on the spatial scan statistic is often use...
Algorithms based on simulating stochastic flows are a simple and natural solution for the problem of clustering graphs, but their widespread use has been hampered by their lack of...
Clustering is one of the most widely used statistical tools for data analysis. Among all existing clustering techniques, k-means is a very popular method because of its ease of pr...
Abstract--Data clustering is a highly used knowledge extraction technique and is applied in more and more application domains. Over the last years, a lot of algorithms have been pr...