Clustering has been one of the most popular methods to discover useful biological insights from DNA microarray. An interesting paradigm is simultaneous clustering of both genes an...
—The conventional K-Means clustering algorithm must know the number of clusters in advance and the clustering result is sensitive to the selection of the initial cluster centroid...
Jing Xiao, YuPing Yan, Ying Lin, Ling Yuan, Jun Zh...
In this paper, we examine the problem of learning from noisecontaminated data in high-dimensional space. A new learning approach based on projections onto multi-dimensional ellips...
Abstract. Semi-supervised clustering models, that incorporate user provided constraints to yield meaningful clusters, have recently become a popular area of research. In this paper...
In this paper two agglomerative learning algorithms based on new similarity measures defined for hyperbox fuzzy sets are proposed. They are presented in a context of clustering and...