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GECCO
2007
Springer
210views Optimization» more  GECCO 2007»
13 years 11 months ago
Mining breast cancer data with XCS
In this paper, we describe the use of a modern learning classifier system to a data mining task. In particular, in collaboration with a medical specialist, we apply XCS to a prima...
Faten Kharbat, Larry Bull, Mohammed Odeh
EC
2006
121views ECommerce» more  EC 2006»
13 years 5 months ago
A Study of Structural and Parametric Learning in XCS
The performance of a learning classifier system is due to its two main components. First, it evolves new structures by generating new rules in a genetic process; second, it adjust...
Tim Kovacs, Manfred Kerber
GECCO
2006
Springer
140views Optimization» more  GECCO 2006»
13 years 8 months ago
A representational ecology for learning classifier systems
The representation used by a learning algorithm introduces a bias which is more or less well-suited to any given learning problem. It is well known that, across all possible probl...
James A. R. Marshall, Tim Kovacs
GECCO
2006
Springer
205views Optimization» more  GECCO 2006»
13 years 8 months ago
Bounding XCS's parameters for unbalanced datasets
This paper analyzes the behavior of the XCS classifier system on imbalanced datasets. We show that XCS with standard parameter settings is quite robust to considerable class imbal...
Albert Orriols-Puig, Ester Bernadó-Mansilla
TEC
2008
115views more  TEC 2008»
13 years 4 months ago
Function Approximation With XCS: Hyperellipsoidal Conditions, Recursive Least Squares, and Compaction
An important strength of learning classifier systems (LCSs) lies in the combination of genetic optimization techniques with gradient-based approximation techniques. The chosen app...
Martin V. Butz, Pier Luca Lanzi, Stewart W. Wilson