The diameter k-clustering problem is the problem of partitioning a finite subset of Rd into k subsets called clusters such that the maximum diameter of the clusters is minimized. ...
EEG segments recorded during microsleep events were transformed to the frequency domain and were subsequently clustered without the common summation of power densities in spectral ...
Independent Variable Group Analysis (IVGA) is a method for grouping dependent variables together while keeping mutually independent or weakly dependent variables in separate group...
We describe a method for identifying different writing styles of online handwritten characters based on clustering. The motivation of this experiment is to develop automatic chara...
Mean-Shift (MS) is a powerful non-parametric clustering method. Although good accuracy can be achieved, its computational cost is particularly expensive even on moderate data sets...