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PRIS
2004
15 years 5 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»
15 years 2 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
15 years 8 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»
15 years 9 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
16 years 5 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