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GECCO
2010
Springer
189views Optimization» more  GECCO 2010»
15 years 11 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...
DAWAK
2003
Springer
15 years 11 months ago
Clustering by Regression Analysis
Abstract In data clustering, many approaches have been proposed. For example, K-means method and hierarchical method. A problem is in effect by initial value and criterion to comb...
Masahiro Motoyoshi, Takao Miura, Isamu Shioya
ESANN
2007
15 years 7 months ago
Feature clustering and mutual information for the selection of variables in spectral data
Spectral data often have a large number of highly-correlated features, making feature selection both necessary and uneasy. A methodology combining hierarchical constrained clusteri...
Catherine Krier, Damien François, Fabrice R...
ICMCS
2006
IEEE
142views Multimedia» more  ICMCS 2006»
16 years 10 days ago
FEMA: A Fast Expectation Maximization Algorithm based on Grid and PCA
EM algorithm is an important unsupervised clustering algorithm, but the algorithm has several limitations. In this paper, we propose a fast EM algorithm (FEMA) to address the limi...
Zhiwen Yu, Hau-San Wong
ICML
2005
IEEE
16 years 7 months ago
Bayesian hierarchical clustering
We present a novel algorithm for agglomerative hierarchical clustering based on evaluating marginal likelihoods of a probabilistic model. This algorithm has several advantages ove...
Katherine A. Heller, Zoubin Ghahramani