A k-means-type algorithm is proposed for efficiently clustering data constrained to lie on the surface of a p-dimensional unit sphere, or data that are mean-zero-unit-variance standardized ...

Advances made to the traditional clustering algorithms solve the various problems such as curse of dimensionality and sparsity of data for multiple attributes. The traditional H-K clustering algorithm ...

Data clustering is the process of placing data items into different groups (clusters) in such a way that items in a particular group are similar to each other and items in different groups are ...

Multivariate analysis in statistics is a set of useful methods for analyzing data when there are more than one variables under consideration. Multivariate analysis techniques may be used for several ...