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AUSDM
2006
Springer
177views Data Mining» more  AUSDM 2006»
15 years 8 months ago
On The Optimal Working Set Size in Serial and Parallel Support Vector Machine Learning With The Decomposition Algorithm
The support vector machine (SVM) is a wellestablished and accurate supervised learning method for the classification of data in various application fields. The statistical learnin...
Tatjana Eitrich, Bruno Lang
AAAI
2008
15 years 6 months ago
Semi-Supervised Ensemble Ranking
Ranking plays a central role in many Web search and information retrieval applications. Ensemble ranking, sometimes called meta-search, aims to improve the retrieval performance b...
Steven C. H. Hoi, Rong Jin
PRIB
2009
Springer
209views Bioinformatics» more  PRIB 2009»
15 years 11 months ago
Class Prediction from Disparate Biological Data Sources Using an Iterative Multi-Kernel Algorithm
For many biomedical modelling tasks a number of different types of data may influence predictions made by the model. An established approach to pursuing supervised learning with ...
Yiming Ying, Colin Campbell, Theodoros Damoulas, M...
GECCO
2007
Springer
149views Optimization» more  GECCO 2007»
15 years 10 months ago
Modeling XCS in class imbalances: population size and parameter settings
This paper analyzes the scalability of the population size required in XCS to maintain niches that are infrequently activated. Facetwise models have been developed to predict the ...
Albert Orriols-Puig, David E. Goldberg, Kumara Sas...
GECCO
2007
Springer
171views Optimization» more  GECCO 2007»
15 years 10 months ago
Toward a better understanding of rule initialisation and deletion
A number of heuristics have been used in Learning Classifier Systems to initialise parameters of new rules, to adjust fitness of parent rules when they generate offspring, and ...
Tim Kovacs, Larry Bull