Sciweavers

100 search results - page 4 / 20
» A Framework for Projected Clustering of High Dimensional Dat...
Sort
View
WIRN
2005
Springer
13 years 10 months ago
Ensembles Based on Random Projections to Improve the Accuracy of Clustering Algorithms
We present an algorithmic scheme for unsupervised cluster ensembles, based on randomized projections between metric spaces, by which a substantial dimensionality reduction is obtai...
Alberto Bertoni, Giorgio Valentini
CIDM
2007
IEEE
13 years 11 months ago
Scalable Clustering for Large High-Dimensional Data Based on Data Summarization
Clustering large data sets with high dimensionality is a challenging data-mining task. This paper presents a framework to perform such a task efficiently. It is based on the notio...
Ying Lai, Ratko Orlandic, Wai Gen Yee, Sachin Kulk...
ECEASST
2010
13 years 2 months ago
Self Organized Swarms for cluster preserving Projections of high-dimensional Data
: A new approach for topographic mapping, called Swarm-Organized Projection (SOP) is presented. SOP has been inspired by swarm intelligence methods for clustering and is similar to...
Alfred Ultsch, Lutz Herrmann
PR
2006
116views more  PR 2006»
13 years 5 months ago
Shared farthest neighbor approach to clustering of high dimensionality, low cardinality data
Clustering algorithms are routinely used in biomedical disciplines, and are a basic tool in bioinformatics. Depending on the task at hand, there are two most popular options, the ...
Stefano Rovetta, Francesco Masulli
ECML
2006
Springer
13 years 9 months ago
Subspace Metric Ensembles for Semi-supervised Clustering of High Dimensional Data
A critical problem in clustering research is the definition of a proper metric to measure distances between points. Semi-supervised clustering uses the information provided by the ...
Bojun Yan, Carlotta Domeniconi