A method is presented to partition a given set of data entries embedded in Euclidean space by recursively bisecting clusters into smaller ones. The initial set is subdivided into ...
Finding clusters with widely differing sizes, shapes and densities in presence of noise and outliers is a challenging job. The DBSCAN is a versatile clustering algorithm that can f...
—A key benefit of utility data centers and cloud computing infrastructures is the level of consolidation they can offer to arbitrary guest applications, and the substantial savi...
Mukil Kesavan, Adit Ranadive, Ada Gavrilovska, Kar...
In solving the classification problem in relational data mining, traditional methods, for example, the C4.5 and its variants, usually require data transformations from datasets sto...
In this paper, we extend the conventional vector quantization by incorporating a vigilance parameter, which steers the tradeoff between plasticity and stability during incremental...