: We present a new iterative method for probabilistic clustering of data. Given clusters, their centers and the distances of data points from these centers, the probability of clus...
A linear multivariate measurement error model AX = B is considered. The errors in A B are row-wise finite dependent, and within each row, the errors may be correlated. Some of th...
Alexander Kukush, Ivan Markovsky, Sabine Van Huffe...
Clustering is the problem of identifying the distribution of patterns and intrinsic correlations in large data sets by partitioning the data points into similarity classes. This p...
DNA microarray experiments generate a substantial amount of information about global gene expression. Gene expression profiles can be represented as points in multi-dimensional sp...
Lu-Yong Wang, Ammaiappan Balasubramanian, Amit Cha...
This paper proposes a clustering method SOMAK, which is composed by Self-Organizing Maps (SOM) followed by the Ant K-means (AK) algorithm. The aim of this method is not to find an...
Jefferson R. Souza, Teresa Bernarda Ludermir, Lean...