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» Agnostic Learning with Ensembles of Classifiers
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KDD
2006
ACM
153views Data Mining» more  KDD 2006»
14 years 8 months ago
Model compression
Often the best performing supervised learning models are ensembles of hundreds or thousands of base-level classifiers. Unfortunately, the space required to store this many classif...
Cristian Bucila, Rich Caruana, Alexandru Niculescu...
ICANN
2007
Springer
14 years 2 months ago
Boosting Unsupervised Competitive Learning Ensembles
Topology preserving mappings are great tools for data visualization and inspection in large datasets. This research presents a combination of several topology preserving mapping mo...
Emilio Corchado, Bruno Baruque, Hujun Yin
GECCO
2009
Springer
150views Optimization» more  GECCO 2009»
14 years 3 months ago
Discrete dynamical genetic programming in XCS
A number of representation schemes have been presented for use within Learning Classifier Systems, ranging from binary encodings to neural networks. This paper presents results fr...
Richard Preen, Larry Bull
EVOW
2008
Springer
13 years 10 months ago
A Hybrid Random Subspace Classifier Fusion Approach for Protein Mass Spectra Classification
Classifier fusion strategies have shown great potential to enhance the performance of pattern recognition systems. There is an agreement among researchers in classifier combination...
Amin Assareh, Mohammad Hassan Moradi, L. Gwenn Vol...
GECCO
2006
Springer
142views Optimization» more  GECCO 2006»
14 years 2 days ago
Classifier prediction based on tile coding
This paper introduces XCSF extended with tile coding prediction: each classifier implements a tile coding approximator; the genetic algorithm is used to adapt both classifier cond...
Pier Luca Lanzi, Daniele Loiacono, Stewart W. Wils...