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» Use of Ensemble Based on GA for Imbalance Problem
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AUSAI
2005
Springer
14 years 1 months ago
Accelerating Real-Valued Genetic Algorithms Using Mutation-with-Momentum
: In a canonical genetic algorithm, the reproduction operators (crossover and mutation) are random in nature. The direction of the search carried out by the GA system is driven pur...
Luke Temby, Peter Vamplew, Adam Berry
AMC
2005
191views more  AMC 2005»
13 years 7 months ago
Model identification of ARIMA family using genetic algorithms
ARIMA is a popular method to analyze stationary univariate time series data. There are usually three main stages to build an ARIMA model, including model identification, model est...
Chorng-Shyong Ong, Jih-Jeng Huang, Gwo-Hshiung Tze...
SAC
1998
ACM
14 years 4 days ago
Scalability of an MPI-based fast messy genetic algorithm
The fast messy genetic algorithm (fmGA) belongs to a class of algorithms inspired by the principles of evolution, known appropriately as "evolutionary algorithms" (EAs)....
Laurence D. Merkle, George H. Gates Jr., Gary B. L...
GECCO
2003
Springer
171views Optimization» more  GECCO 2003»
14 years 1 months ago
Genetic Algorithm Optimized Feature Transformation - A Comparison with Different Classifiers
When using a Genetic Algorithm (GA) to optimize the feature space of pattern classification problems, the performance improvement is not only determined by the data set used, but a...
Zhijian Huang, Min Pei, Erik D. Goodman, Yong Huan...
IJCAI
2007
13 years 9 months ago
Ensembles of Partially Trained SVMs with Multiplicative Updates
The training of support vector machines (SVM) involves a quadratic programming problem, which is often optimized by a complicated numerical solver. In this paper, we propose a muc...
Ivor W. Tsang, James T. Kwok