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» Adapting the Fitness Function in GP for Data Mining
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EUROGP
1999
Springer
166views Optimization» more  EUROGP 1999»
13 years 11 months ago
Adapting the Fitness Function in GP for Data Mining
In this paper we describe how the Stepwise Adaptation of Weights (saw) technique can be applied in genetic programming. The saw-ing mechanism has been originally developed for and ...
Jeroen Eggermont, A. E. Eiben, Jano I. van Hemert
ICDM
2010
IEEE
264views Data Mining» more  ICDM 2010»
13 years 5 months ago
Block-GP: Scalable Gaussian Process Regression for Multimodal Data
Regression problems on massive data sets are ubiquitous in many application domains including the Internet, earth and space sciences, and finances. In many cases, regression algori...
Kamalika Das, Ashok N. Srivastava
EUROGP
2007
Springer
161views Optimization» more  EUROGP 2007»
14 years 1 months ago
Mining Distributed Evolving Data Streams Using Fractal GP Ensembles
A Genetic Programming based boosting ensemble method for the classification of distributed streaming data is proposed. The approach handles flows of data coming from multiple loc...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...
GECCO
2006
Springer
148views Optimization» more  GECCO 2006»
13 years 11 months ago
Behavioural GP diversity for dynamic environments: an application in hedge fund investment
We present a new mechanism for preserving phenotypic behavioural diversity in a Genetic Programming application for hedge fund portfolio optimization, and provide experimental res...
Wei Yan, Christopher D. Clack
CEC
2010
IEEE
12 years 11 months ago
Tweaking a tower of blocks leads to a TMBL: Pursuing long term fitness growth in program evolution
— If a population of programs evolved not for a few hundred generations but for a few hundred thousand or more, could it generate more interesting behaviours and tackle more comp...
Tony E. Lewis, George D. Magoulas