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Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06)
Imbalanced Datasets Classification by Fuzzy Rule Extraction and Genetic Algorithms
Hong Kong, China
December 18-December 22
ISBN: 0-7695-2702-7
ASCII Text
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Vicenc Soler, Jesus Cerquides, Josep Sabria, Jordi Roig, Marta Prim, "Imbalanced Datasets Classification by Fuzzy Rule Extraction and Genetic Algorithms," Data Mining Workshops, International Conference on, pp. 330-336, Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06), 2006.
 
 
BibTex
x
 
@article{ 10.1109/ICDMW.2006.95,
author = {Vicenc Soler and Jesus Cerquides and Josep Sabria and Jordi Roig and Marta Prim},
title = {Imbalanced Datasets Classification by Fuzzy Rule Extraction and Genetic Algorithms},
journal ={Data Mining Workshops, International Conference on},
volume = {0},
year = {2006},
isbn = {0-7695-2702-7},
pages = {330-336},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICDMW.2006.95},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Data Mining Workshops, International Conference on
TI - Imbalanced Datasets Classification by Fuzzy Rule Extraction and Genetic Algorithms
SN - 0-7695-2702-7
SP330
EP336
A1 - Vicenc Soler,
A1 - Jesus Cerquides,
A1 - Josep Sabria,
A1 - Jordi Roig,
A1 - Marta Prim,
PY - 2006
KW - null
VL - 0
JA - Data Mining Workshops, International Conference on
ER -
 
Vicenc Soler, Universitat Aut?noma de Barcelona
Jesus Cerquides, University of Barcelona
Josep Sabria, Hospital Universitari Dr.Josep Trueta, Spain
Jordi Roig, Universitat Aut?noma de Barcelona, Spain
Marta Prim, Universitat Aut?noma de Barcelona, Spain
We propose a method based on the extraction of fuzzy rules by genetic algorithms for the classification of imbalanced datasets when understandability is an issue. We propose a new method for fuzzy variable construction based on modifying the set of fuzzy variables obtained by the RecBF/DDA algorithm. Later, these variables are recombined to obtain fuzzy rules by means of a Genetic Algorithm. The method has been developed for the detection of Down?s syndrome in fetus. We provide empirical results showing its accuracy for this task. Furthermore, we provide more generic experimental results over UCI datasets proving that the method can have a wider applicability.
Citation:
Vicenc Soler, Jesus Cerquides, Josep Sabria, Jordi Roig, Marta Prim, "Imbalanced Datasets Classification by Fuzzy Rule Extraction and Genetic Algorithms," icdmw, pp.330-336, Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06), 2006
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