Clustering Algorithms
Get flash to fully experience Pearltrees
An approach to overcome the limits of K-means
Time ago, I posted a banal case to show the limits of K-mean clustering.Many structured data of scientific interest can be represented as networks, where sets of nodes or vertices joined together in pairs by links or edges. Although these networks may belong to different research areas, there is one property that many of them do have in common: the network community structure, which means that there exists densely connected groups of vertices, with only sparser connections between groups.
CMPUT 695 Knowledge Discovery in Data
www.isip.piconepress.com/publications/courses/msstate/.../lectur
Mathematics Libraries
The Kohonen Self-Organizing Feature Map (SOFM or SOM) is a clustering and data visualization technique based on a neural network viewpoint.
Data Mining Algorithms In R/Clustering/Self-Organizing Maps (SOM) - Wikibooks, open books for an open world
Clustering can be considered the most important unsupervised learning problem; so, as every other problem of this kind, it deals with finding a structure in a collection of unlabeled data. A loose definition of clustering could be “the process of organizing objects into groups whose members are similar in some way”. A cluster is therefore a collection of objects which are “similar” between them and are “dissimilar” to the objects belonging to other clusters.
