Reducing the Complexity of Genetic Fuzzy Classifiers in Highly-Dimensional Classification Problems
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
1 Online-Ressource.
- Language
-
Englisch
- Bibliographic citation
-
Reducing the Complexity of Genetic Fuzzy Classifiers in Highly-Dimensional Classification Problems ; volume:5 ; number:2 ; day:1 ; month:4 ; year:2012 ; pages:254-275 ; date:4.2012
International journal of computational intelligence systems ; 5, Heft 2 (1.4.2012), 254-275, 4.2012
- Creator
-
Stavrakoudis, Dimitris G.
Galidaki, Georgia N.
Gitas, Ioannis Z.
Theocharis, John B.
- Contributor
-
SpringerLink (Online service)
- DOI
-
10.1080/18756891.2012.685290
- URN
-
urn:nbn:de:101:1-2024031113394204685235
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
14.08.2025, 10:45 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Stavrakoudis, Dimitris G.
- Galidaki, Georgia N.
- Gitas, Ioannis Z.
- Theocharis, John B.
- SpringerLink (Online service)
Other Objects (12)
Equalizing imbalanced imprecise datasets for genetic fuzzy classifiers
An Approach to Reducing Input Parameter Volume for Fault Classifiers
OPTIMISATION OF FUZZY BASED SOFT CLASSIFIERS FOR REMOTE SENSING DATA
Fuzzy classifiers and their relation to cluster analysis and neural networks
Offline recognition of degraded numeral characters with MMTD-based fuzzy classifiers
Object detection using ensemble of linear classifiers with fuzzy adaptive boosting
Fuzzy classifiers and their relation to cluster analysis and neural networks
Reducing the complexity of large EPCs
Specific Classifiers.
Reducing the complexity of OMICS data analysis
Reducing the complexity of OMICS data analysis
Effect of fuzziness in fuzzy rule-based classifiers defined by strong fuzzy partitions and winner-takes-all inference
Equalizing imbalanced imprecise datasets for genetic fuzzy classifiers
An Approach to Reducing Input Parameter Volume for Fault Classifiers
OPTIMISATION OF FUZZY BASED SOFT CLASSIFIERS FOR REMOTE SENSING DATA
Fuzzy classifiers and their relation to cluster analysis and neural networks
Offline recognition of degraded numeral characters with MMTD-based fuzzy classifiers
Object detection using ensemble of linear classifiers with fuzzy adaptive boosting
Fuzzy classifiers and their relation to cluster analysis and neural networks
Reducing the complexity of large EPCs
Specific Classifiers.
Reducing the complexity of OMICS data analysis
Reducing the complexity of OMICS data analysis
Effect of fuzziness in fuzzy rule-based classifiers defined by strong fuzzy partitions and winner-takes-all inference
Equalizing imbalanced imprecise datasets for genetic fuzzy classifiers
An Approach to Reducing Input Parameter Volume for Fault Classifiers
OPTIMISATION OF FUZZY BASED SOFT CLASSIFIERS FOR REMOTE SENSING DATA
Fuzzy classifiers and their relation to cluster analysis and neural networks
Offline recognition of degraded numeral characters with MMTD-based fuzzy classifiers
Object detection using ensemble of linear classifiers with fuzzy adaptive boosting
Fuzzy classifiers and their relation to cluster analysis and neural networks
Reducing the complexity of large EPCs
Specific Classifiers.
Reducing the complexity of OMICS data analysis
Reducing the complexity of OMICS data analysis