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» Adapting the Fitness Function in GP for Data Mining
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GECCO
1999
Springer
167views Optimization» more  GECCO 1999»
13 years 11 months ago
A Biologically Inspired Fitness Function for Robotic Grasping
This paper describes the innovative use of genetic programming (GP) to solve the grasp synthesis problem for multifingered robot hands. The goal of our algorithm is to select a Ò...
J. Jaime Fernandez, Ian D. Walker
CEC
2010
IEEE
13 years 8 months ago
Improving GP classification performance by injection of decision trees
This paper presents a novel hybrid method combining genetic programming and decision tree learning. The method starts by estimating a benchmark level of reasonable accuracy, based ...
Rikard König, Ulf Johansson, Tuve Löfstr...
GPEM
2000
121views more  GPEM 2000»
13 years 7 months ago
Bayesian Methods for Efficient Genetic Programming
ct. A Bayesian framework for genetic programming GP is presented. This is motivated by the observation that genetic programming iteratively searches populations of fitter programs ...
Byoung-Tak Zhang
ICTAI
2007
IEEE
14 years 1 months ago
An Adaptive Distributed Ensemble Approach to Mine Concept-Drifting Data Streams
An adaptive boosting ensemble algorithm for classifying homogeneous distributed data streams is presented. The method builds an ensemble of classifiers by using Genetic Programmi...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...
ACSW
2004
13 years 9 months ago
Applying Online Gradient Descent Search to Genetic Programming for Object Recognition
This paper describes an approach to the use of gradient descent search in genetic programming (GP) for object classification problems. In this approach, pixel statistics are used ...
William D. Smart, Mengjie Zhang