Schedule
Click here to download the general program
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9:30-10:45 |
Plenary Lecture |
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Introduced by Francisco Herrera |
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Data Complexity: An Overview and New Challenges
T.K. Ho, Bell Laboratories, USA
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10:45 - 11:15 Coffee break |
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11:15 - 12:40 |
Session I. Studies on Data Complexity |
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Chairman: E. Bernado |
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On the necessity of dataset characterization for experimental analysis.Towards artificial datasets
Nuria Macia, URL, Barcelona 
Some studies on the construction of artificial data sets for some data complexity measures.
José Ramón Cano, UJ, Jaén
Evolutionary prototype selection evaluated with an overlapping measure
José Ramón Cano, UJ, Jaén
Open discussion on Data Compexity and future work
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Part II: Classification with Imbalanced Data Sets |
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12:40 - 14:00 |
Session I: Classification with Imbalanced Data Sets |
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Chairman: J.A. Gámez |
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Introduction to Imbalanced data sets. Some results on the use of evolutionary prototype selection for imbalanced data sets
Salvador García, UGR, Granada
Some results on the use of UCS for imbalanced data sets
Albert Orriols, URL, Barcelona
Some results on the use of Fuzzy Rule Based Systems for imbalanded data sets
Alberto Fernández, UGR, Granada
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Part III. Genetics-based Machine Learning |
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16:00 - 17:30 |
Session I: Genetics-based Machine Learning. Pitts and IRL approaches |
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Chairman: L. Sánchez |
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Memetic Pittsburgh LCS
Jaume Barcardit, The University of Nottingham
HIDER Method and natural codification
Raul Giráldez, UPO, Sevilla
A study of statistical techniques and performance of GBML
Julián Luengo, UGR, Granada
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17:30 - 18:00 Coffee break |
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18:00 - 19:00 |
Session II: Genetics-based Machine Learning. Michigan approches |
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Chairman: J. Bacardit |
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Incorporating fuzzy rules in LCS: Fuzzy XCS and Fuzzy UCS
Jorge Casillas, UGR, Granada
LCS: New trends
18:30 Albert Orriols, URL, Barcelona
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Part IV. Genetics-based Machine Learning. Large-scale datasets |
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19:00 - 20:30 |
Session I: Genetics-based Machine Learning. Large-scale datasets |
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Chairman: A. Orriols |
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GBML methods for large-scale datasets
Jaume Bacardit, The University of Nottingham
GP-COACH: Genetic Programming based learning of COmpact and ACcurate fuzzy rule based classification systems for High dimensional problems
Francisco Berlanga, UJ, Jaén
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21:15 Dinner at Paco Restaurant |
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Part IV: Knowledge Extraction based on Evolutionary Learning: Some Data Mining Problems |
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9:00 - 10:30 |
Session I: Knowledge Extraction based on Evolutionary Learning: Some Data Mining Problems |
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Chairman: R. Alcalá |
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Multi-instance learning.
Introduction to Multi-instance learning: Foundations and applications. Some results on the use of Genetic Programming for MIL.
Amelia Zafra, UCO, Córdoba
Using EDAs for Learning.
Introduction to EDAs. Learning linguistic fuzzy rules with EDAs: an application to breeding value prediction in Manchego sheep.
José Antonio Gámez, UCLM, Albacete
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10:30 - 11:00 Coffee break |
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11:00 - 12:30 |
Session II: Knowledge Extraction based on Evolutionary Learning: Some Data Mining Problems (cont.) |
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Chairman: J. Casillas |
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Subgroup Discovery.
Introduction to Subgroup Discovery. Some results on the evolutionary extraction of fuzzy rules for subgroup discovery
Pedro González, UJ, Jaén
Low quality data.
Introduction to Low quality data. Some results on the use of Evolutionary Algorithms for extraction knowledge from low quality data
Luciano Sánchez, UO, Gijón
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Part III: Genetics-based Machine Learning (cont.). |
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12:30 - 14:15 |
Session III: Genetics-based Machine Learning. Multiobjective learning |
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Chairman: F. Herrera |
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Introduction to Multi-objective Learning.
Some resuls on the use of MOEAs for tuning FRBSs parameters
Rafael Alcalá, UGR, Granada
Towards evolving consistent, complete and compact fuzzy rule sets: A genetic multiobjective approach
Jorge Casillas, UGR, Granada
Open discussion on Knowledge Extraction based on Evolutionary Learning. GBML new research directions. Cooperation between the research groups
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14:15 - 14:30 Workshop Closure |
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