Although very widely used in unsupervised data mining, most clustering methods are affected by the instability of the resulting clusters w.r.t. the initialization of the algorithm ...
—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...
Event logs or log files form an essential part of any network management and administration setup. While log files are invaluable to a network administrator, the vast amount of dat...
Adetokunbo Makanju, Stephen Brooks, A. Nur Zincir-...
Clustering is often formulated as the maximum likelihood estimation of a mixture model that explains the data. The EM algorithm widely used to solve the resulting optimization pro...
We present a novel multiscale clustering algorithm inspired by algebraic multigrid techniques. Our method begins with assembling data points according to local similarities. It us...