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EUROGP
2004
Springer
133views Optimization» more  EUROGP 2004»
13 years 10 months ago
Lymphoma Cancer Classification Using Genetic Programming with SNR Features
Lymphoma cancer classification with DNA microarray data is one of important problems in bioinformatics. Many machine learning techniques have been applied to the problem and produc...
Jin-Hyuk Hong, Sung-Bae Cho
JUCS
2008
160views more  JUCS 2008»
13 years 4 months ago
Automatic Construction of Fuzzy Rule Bases: a further Investigation into two Alternative Inductive Approaches
: The definition of the Fuzzy Rule Base is one of the most important and difficult tasks when designing Fuzzy Systems. This paper discusses the results of two different hybrid meth...
Marcos Evandro Cintra, Heloisa de Arruda Camargo, ...
ICML
1998
IEEE
14 years 5 months ago
Genetic Programming and Deductive-Inductive Learning: A Multi-Strategy Approach
Genetic Programming (GP) is a machine learning technique that was not conceived to use domain knowledge for generating new candidate solutions. It has been shown that GP can bene ...
Ricardo Aler, Daniel Borrajo, Pedro Isasi
MDAI
2005
Springer
13 years 10 months ago
Cancer Prediction Using Diversity-Based Ensemble Genetic Programming
Combining a set of classifiers has often been exploited to improve the classification performance. Accurate as well as diverse base classifiers are prerequisite to construct a good...
Jin-Hyuk Hong, Sung-Bae Cho
EPS
1998
Springer
13 years 9 months ago
Genetic Programming for Automatic Target Classification and Recognition
We use the genetic programming (GP) paradigm for two tasks. The first task given a GP is the generation of rules for the target / clutter classification of a set of synthetic apert...
Stephen A. Stanhope, Jason M. Daida