Parallel data mining-case study
(2010)
Report
Professor Matthew Studley's Outputs (6)
Learning classifier system ensembles with rule-sharing (2007)
Journal Article
This paper presents an investigation into exploiting the population-based nature of learning classifier systems (LCSs) for their use within highly parallel systems. In particular, the use of simple payoff and accuracy-based LCSs within the ensemble m... Read More about Learning classifier system ensembles with rule-sharing.
A comparison of DWT/PAA and DFT for time series classification (2006)
Presentation / Conference Contribution
Discrete Fourier transforms (DFT) and Haar two, PAA is identical to a Haar Wavelet transformation [61. wavelets (DWT) were proposed for the use in time series data mining over five years ago and have since proved to be popular algorithms for the tran... Read More about A comparison of DWT/PAA and DFT for time series classification.
On the use of rule-sharing in learning classifier system ensembles (2005)
Presentation / Conference Contribution
Attribute selection methods for filtered attribute subspace based bagging with injected randomness (FASBIR) (2005)
Presentation / Conference Contribution
Consideration of multiple objectives in neural learning classifier systems (2002)
Presentation / Conference Contribution
© Springer-Verlag Berlin Heidelberg 2002. For effective use in a number of problem domains Learning Classifier Systems must be able to manage multiple objectives. This paper explicitly considers the case of developing the controller for a simulated m... Read More about Consideration of multiple objectives in neural learning classifier systems.