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ICANN
2010
Springer
13 years 1 months ago
Using Evolutionary Multiobjective Techniques for Imbalanced Classification Data
The aim of this paper is to study the use of Evolutionary Multiobjective Techniques to improve the performance of Neural Networks (NN). In particular, we will focus on classificati...
Sandra García, Ricardo Aler, Inés Ma...
HIS
2008
13 years 5 months ago
Evolutionary Training Set Selection to Optimize C4.5 in Imbalanced Problems
Classification in imbalanced domains is a recent challenge in machine learning. We refer to imbalanced classification when data presents many examples from one class and few from ...
Salvador García, Francisco Herrera
FLAIRS
2008
13 years 6 months ago
Building Useful Models from Imbalanced Data with Sampling and Boosting
Building useful classification models can be a challenging endeavor, especially when training data is imbalanced. Class imbalance presents a problem when traditional classificatio...
Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van H...
EVOW
2006
Springer
13 years 8 months ago
Mining Structural Databases: An Evolutionary Multi-Objetive Conceptual Clustering Methodology
Abstract. The increased availability of biological databases containing representations of complex objects permits access to vast amounts of data. In spite of the recent renewed in...
Rocío Romero-Záliz, Cristina Rubio-E...
GECCO
2006
Springer
165views Optimization» more  GECCO 2006»
13 years 8 months ago
Multiobjective genetic rule selection as a data mining postprocessing procedure
In this paper, we show the usefulness of multiobjective genetic rule selection as a postprocessing procedure in data mining for pattern classification problems. First we extract a...
Hisao Ishibuchi, Yusuke Nojima, Isao Kuwajima