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IJAR
2008
88views more  IJAR 2008»
15 years 16 days ago
Clustering decomposed belief functions using generalized weights of conflict
We develop a method for clustering all types of belief functions, in particular non-consonant belief functions. Such clustering is done when the belief functions concern multiple ...
Johan Schubert
BMCBI
2008
122views more  BMCBI 2008»
15 years 19 days ago
A practical comparison of two K-Means clustering algorithms
Background: Data clustering is a powerful technique for identifying data with similar characteristics, such as genes with similar expression patterns. However, not all implementat...
Gregory A. Wilkin, Xiuzhen Huang
PR
2008
123views more  PR 2008»
15 years 14 days ago
Extensions of vector quantization for incremental clustering
In this paper, we extend the conventional vector quantization by incorporating a vigilance parameter, which steers the tradeoff between plasticity and stability during incremental...
Edwin Lughofer
SIAMSC
2008
159views more  SIAMSC 2008»
15 years 13 days ago
Hierarchical Clustering of Massive, High Dimensional Data Sets by Exploiting Ultrametric Embedding
Coding of data, usually upstream of data analysis, has crucial implications for the data analysis results. By modifying the data coding
Fionn Murtagh, Geoff Downs, Pedro Contreras