pivmet: Pivotal methods for Bayesian relabelling and k-means clustering
The identification of groups' prototypes, ie elements of a dataset that represent different
groups of data points, may be relevant to the tasks of clustering, classification and mixture …
groups of data points, may be relevant to the tasks of clustering, classification and mixture …
[PDF][PDF] K-means seeding via MUS algorithm
K-means algorithm is one of the most popular procedures in data clustering. Despite its
large use, one major criticism is the impact of the initial seeding on the final solution. We …
large use, one major criticism is the impact of the initial seeding on the final solution. We …
Consensus clustering via pivotal methods
We propose an approach to the cluster ensemble problem based on pivotal units extracted
from a co-association matrix. It can be seen as a modified version of K-means method, which …
from a co-association matrix. It can be seen as a modified version of K-means method, which …
[PDF][PDF] Pivotal seeding for K-means based on clustering ensembles
Despite its large use, one major limitation of K-means algorithm is the impact of the initial
seeding on the final partition. We propose a modified version, using the information …
seeding on the final partition. We propose a modified version, using the information …