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» Genetic Algorithm based Selective Neural Network Ensemble
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IJCNN
2007
IEEE
14 years 2 months ago
Random Feature Subset Selection for Analysis of Data with Missing Features
Abstract - We discuss an ensemble-of-classifiers based algorithm for the missing feature problem. The proposed approach is inspired in part by the random subspace method, and in pa...
Joseph DePasquale, Robi Polikar
BMCBI
2010
108views more  BMCBI 2010»
13 years 8 months ago
A genetic ensemble approach for gene-gene interaction identification
Background: It has now become clear that gene-gene interactions and gene-environment interactions are ubiquitous and fundamental mechanisms for the development of complex diseases...
Pengyi Yang, Joshua W. K. Ho, Albert Y. Zomaya, Bi...
ESWA
2006
154views more  ESWA 2006»
13 years 8 months ago
Artificial neural networks with evolutionary instance selection for financial forecasting
In this paper, I propose a genetic algorithm (GA) approach to instance selection in artificial neural networks (ANNs) for financial data mining. ANN has preeminent learning abilit...
Kyoung-jae Kim
ICONIP
2008
13 years 10 months ago
The Diversity of Regression Ensembles Combining Bagging and Random Subspace Method
Abstract. The concept of Ensemble Learning has been shown to increase predictive power over single base learners. Given the bias-variancecovariance decomposition, diversity is char...
Alexandra Scherbart, Tim W. Nattkemper
IWANN
2011
Springer
12 years 11 months ago
A Preliminary Study on the Use of Fuzzy Rough Set Based Feature Selection for Improving Evolutionary Instance Selection Algorith
In recent years, the increasing interest in fuzzy rough set theory has allowed the definition of novel accurate methods for feature selection. Although their stand-alone applicati...
Joaquín Derrac, Chris Cornelis, Salvador Ga...