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» Random Projections for $k$-means Clustering
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PAKDD
2009
ACM
209views Data Mining» more  PAKDD 2009»
14 years 4 months ago
Approximate Spectral Clustering.
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-...
Christopher Leckie, James C. Bezdek, Kotagiri Rama...
MCS
2007
Springer
14 years 1 months ago
Selecting Diversifying Heuristics for Cluster Ensembles
Abstract. Cluster ensembles are deemed to be better than single clustering algorithms for discovering complex or noisy structures in data. Various heuristics for constructing such ...
Stefan Todorov Hadjitodorov, Ludmila I. Kuncheva
ECML
2004
Springer
14 years 23 days ago
The Principal Components Analysis of a Graph, and Its Relationships to Spectral Clustering
This work presents a novel procedure for computing (1) distances between nodes of a weighted, undirected, graph, called the Euclidean Commute Time Distance (ECTD), and (2) a subspa...
Marco Saerens, François Fouss, Luh Yen, Pie...
BMCBI
2007
128views more  BMCBI 2007»
13 years 7 months ago
Model order selection for bio-molecular data clustering
Background: Cluster analysis has been widely applied for investigating structure in bio-molecular data. A drawback of most clustering algorithms is that they cannot automatically ...
Alberto Bertoni, Giorgio Valentini
CIBB
2008
13 years 9 months ago
Unsupervised Stability-Based Ensembles to Discover Reliable Structures in Complex Bio-molecular Data
The assessment of the reliability of clusters discovered in bio-molecular data is a central issue in several bioinformatics problems. Several methods based on the concept of stabil...
Alberto Bertoni, Giorgio Valentini