|
|
|
|
|
Libero Nigro and Pasi Fränti
This paper proposes two algorithms for clustering data, which are variable-sized sets of elementary items. An example of such data occurs in the analysis of a medical diagnosis, where the goal is to detect human subjects who share common diseases to poss...
ver más
|
|
|
|
|
|
|
|
|
|
|
Libero Nigro and Franco Cicirelli
K-Means is a ?de facto? standard clustering algorithm due to its simplicity and efficiency. K-Means, though, strongly depends on the initialization of the centroids (seeding method) and often gets stuck in a local sub-optimal solution. K-Means, in fact, ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Libero Nigro
K-means is a well-known clustering algorithm often used for its simplicity and potential efficiency. Its properties and limitations have been investigated by many works reported in the literature. K-means, though, suffers from computational problems when...
ver más
|
|
|
|
|
|