Conference paper

HLOSTA Martin, STRÍŽ Rostislav, ZENDULKA Jaroslav and HRUŠKA Tomáš. PSO-based Constrained Imbalanced Data Classification. In: Proceedings of the Twelth International Conference on Informatics INFORMATICS'2013. Spišská Nová Ves: The University of Technology Košice, 2013, pp. 234-239. ISBN 978-80-8143-127-2.
Publication language:english
Original title:PSO-based Constrained Imbalanced Data Classification
Title (cs):Klasifikace nevyvážených dat s omezením založená na PSO
Proceedings:Proceedings of the Twelth International Conference on Informatics INFORMATICS'2013
Conference:Informatics 2013 - 12th International Scientific Conference on Informatics
Place:Spišská Nová Ves, SK
Publisher:The University of Technology Košice
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Data mining, imbalance classification, constraints, PSO, Genetic Algorithm
The paper deals with classification of highly imbalanced data with accuracy constraints for the minority class. We solve this problem by our proposed meta-learning method that uses cost-sensitive logistic regression to generate initial candidate models. These models can be used as an initial solutions for various optimization algorithms. This paper is aimed for using Particle Swarm Optimization (PSO) to handle the constrained imbalanced classification problem. Experiments, comparing with Genetic Algorithm (GA), show that the swarm intelligence approach is suitable for this problem and outperforms GA.
   author = {Martin Hlosta and Rostislav Str{\'{i}}{\v{z}} and Jaroslav
	Zendulka and Tom{\'{a}}{\v{s}} Hru{\v{s}}ka},
   title = {PSO-based Constrained Imbalanced Data Classification},
   pages = {234--239},
   booktitle = {Proceedings of the Twelth International Conference on
	Informatics INFORMATICS'2013},
   year = {2013},
   location = {Spi{\v{s}}sk{\'{a}} Nov{\'{a}} Ves, SK},
   publisher = {The University of Technology Ko{\v{s}}ice},
   ISBN = {978-80-8143-127-2},
   language = {english},
   url = {}

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