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ADMA
2006
Springer
127views Data Mining» more  ADMA 2006»
16 years 22 days ago
Feature Selection for Complex Patterns
Feature selection is an important data preprocessing step in data mining and pattern recognition. Many algorithms have been proposed in the past for simple patterns that can be cha...
Peter Schenkel, Wanqing Li, Wanquan Liu
GECCO
2008
Springer
131views Optimization» more  GECCO 2008»
15 years 7 months ago
Rigorous analyses of fitness-proportional selection for optimizing linear functions
Rigorous runtime analyses of evolutionary algorithms (EAs) mainly investigate algorithms that use elitist selection methods. Two algorithms commonly studied are Randomized Local S...
Edda Happ, Daniel Johannsen, Christian Klein, Fran...
PAMI
2007
156views more  PAMI 2007»
15 years 6 months ago
Selection and Fusion of Color Models for Image Feature Detection
—The choice of a color model is of great importance for many computer vision algorithms (e.g., feature detection, object recognition, and tracking) as the chosen color model indu...
Harro M. G. Stokman, Theo Gevers
KDD
2009
ACM
180views Data Mining» more  KDD 2009»
16 years 7 months ago
Consensus group stable feature selection
Stability is an important yet under-addressed issue in feature selection from high-dimensional and small sample data. In this paper, we show that stability of feature selection ha...
Steven Loscalzo, Lei Yu, Chris H. Q. Ding
GECCO
2005
Springer
126views Optimization» more  GECCO 2005»
16 years 8 days ago
Is negative selection appropriate for anomaly detection?
Negative selection algorithms for hamming and real-valued shape-spaces are reviewed. Problems are identified with the use of these shape-spaces, and the negative selection algori...
Thomas Stibor, Philipp H. Mohr, Jonathan Timmis, C...