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PRIS
2004
13 years 7 months ago
Comparison of Combination Methods using Spectral Clustering Ensembles
We address the problem of the combination of multiple data partitions, that we call a clustering ensemble. We use a recent clustering approach, known as Spectral Clustering, and th...
André Lourenço, Ana L. N. Fred
ICDM
2010
IEEE
125views Data Mining» more  ICDM 2010»
13 years 3 months ago
Evolving Ensemble-Clustering to a Feedback-Driven Process
Abstract--Data clustering is a highly used knowledge extraction technique and is applied in more and more application domains. Over the last years, a lot of algorithms have been pr...
Martin Hahmann, Dirk Habich, Wolfgang Lehner
DIS
2006
Springer
13 years 9 months ago
A Novel Framework for Discovering Robust Cluster Results
We propose a novel method, called heterogeneous clustering ensemble (HCE), to generate robust clustering results that combine multiple partitions (clusters) derived from various cl...
Hye-Sung Yoon, Sang-Ho Lee, Sung-Bum Cho, Ju Han K...
GECCO
2010
Springer
189views Optimization» more  GECCO 2010»
13 years 10 months ago
Knowledge mining with genetic programming methods for variable selection in flavor design
This paper presents a novel approach for knowledge mining from a sparse and repeated measures dataset. Genetic programming based symbolic regression is employed to generate multip...
Katya Vladislavleva, Kalyan Veeramachaneni, Matt B...
ICPR
2006
IEEE
14 years 6 months ago
Learning Pairwise Similarity for Data Clustering
Each clustering algorithm induces a similarity between given data points, according to the underlying clustering criteria. Given the large number of available clustering technique...
Ana L. N. Fred, Anil K. Jain