Genetic Programming Bibliography entries for Sebastian Ventura

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GP coauthors/coeditors: Jose Luis Avila-Jimenez, Eva L Gibaja, Amelia Zafra Gomez, Rafael Barbudo Lunar, Jose Raul Romero Salguero, Alberto Cano Rojas, Juan Luis Olmo, Jose Maria Luna, Krzysztof J Cios, Jose Antonio Delgado Osuna, Carlos Garcia-Martinez, Pedro Gonzalez Espejo, Cesar Hervas Martinez, Cristobal Romero Morales, Francisco Herrera, Alain Guerrero-Enamorado, Carlos Morell, Amin Yousef Mohammad Noaman, Aurora Ramirez Quesada, Mykola Pechenizkiy, Maria Jose del Jesus, Francisco Padillo, Wouter Duivesteijn, Philippe Fournier-Viger, Carlos Marquez-Vera, Jose M Moyano, Oscar Gabriel Reyes Pupo, Habib M Fardoun, Abdul Hamid Mohamed Ragab, David Pinheiro, Luis A Quintero-Dominguez, Jose Maria Moyano Murillo, Paul De Bra, Jose Antonio Delgado Molina, Enrique Herrera Viedma,

Genetic Programming Articles by Sebastian Ventura

  1. Jose M. Moyano and Sebastian Ventura. Auto-adaptive Grammar-Guided Genetic Programming algorithm to build Ensembles of Multi-Label Classifiers. Information Fusion, 78:1-19, 2022. details

  2. Jose M. Moyano and Oscar Gabriel Reyes Pupo and Habib M. Fardoun and Sebastian Ventura. Performing multi-target regression via gene expression programming-based ensemble models. Neurocomputing, 432:275-287, 2021. details

  3. Luis A. Quintero-Dominguez and Carlos Morell and Sebastian Ventura. A propositionalization method of multi-relational data based on Grammar-Guided Genetic Programming. Expert Systems with Applications, 168:114263, 2021. details

  4. Jose Maria Luna and Philippe Fournier-Viger and Sebastian Ventura. Extracting User-Centric Knowledge on Two Different Spaces: Concepts and Records. IEEE Access, 8:134782-134799, 2020. details

  5. Jose Maria Luna and Mykola Pechenizkiy and Wouter Duivesteijn and Sebastian Ventura. Exceptional in so Many Ways--Discovering Descriptors That Display Exceptional Behavior on Contrasting Scenarios. IEEE Access, 8:200982-200994, 2020. details

  6. Carlos Garcia-Martinez and Sebastian Ventura. Multi-view Genetic Programming Learning to Obtain Interpretable Rule-Based Classifiers for Semi-supervised Contexts. Lessons Learnt. International Journal of Computational Intelligence Systems, 13(1):576-590, 2020. details

  7. Francisco Padillo and Jose Maria Luna and Sebastian Ventura. A Grammar-Guided Genetic Programing Algorithm for Associative Classification in Big Data. Cognitive Computation, 11:331-346, 2019. details

  8. Francisco Padillo and Jose Maria Luna and Francisco Herrera and Sebastian Ventura. Mining association rules on Big Data through MapReduce genetic programming. Integrated Computer-Aided Engineering,, 25(1):31-48, 2018. details

  9. Jose Maria Luna and Mykola Pechenizkiy and Maria Jose del Jesus and Sebastian Ventura. Mining Context-Aware Association Rules Using Grammar-Based Genetic Programming. IEEE Transactions on Cybernetics, 48(11):3030-3044, 2018. details

  10. Alain Guerrero-Enamorado and Carlos Morell and Sebastian Ventura. A gene expression programming algorithm for discovering classification rules in the multi-objective space. International Journal of Computational Intelligence Systems, 11(1):540-559, 2018. details

  11. Alberto Cano and Sebastian Ventura and Krzysztof J. Cios. Multi-objective genetic programming for feature extraction and data visualization. Soft Computing, 21(8):2069-2089, 2017. details

  12. Jose Maria Luna and Mykola Pechenizkiy and Sebastian Ventura. Mining exceptional relationships with grammar-guided genetic programming. Knowledge and Information Systems, 47(3):571-594, 2016. details

  13. Aurora Ramirez and Jose Raul Romero and Sebastian Ventura. A comparative study of many-objective evolutionary algorithms for the discovery of software architectures. Empirical Software Engineering, 21(6):2546-2600, 2016. details

  14. Amin Y. Noaman and Jose Maria Luna and Abdul Hamid M. Ragab and Sebastian Ventura. Recommending degree studies according to students' attitudes in high school by means of subgroup discovery. International Journal of Computational Intelligence Systems, 9(6):1101-1117, 2016. details

  15. Alain Guerrero-Enamorado and Carlos Morell and Amin Y. Noaman and Sebastian Ventura. An Algorithm Evaluation for Discovering Classification Rules with Gene Expression Programming. International Journal of Computational Intelligence Systems, 9(2):263-280, 2016. details

  16. Alberto Cano and Jose Maria Luna and Amelia Zafra and Sebastian Ventura. A Classification Module for Genetic Programming Algorithms in JCLEC. Journal of Machine Learning Research, 16:491-494, 2015. details

  17. Alberto Cano and Amelia Zafra and Sebastian Ventura. Speeding up multiple instance learning classification rules on GPUs. Knowledge and Information Systems, 44(1):127-145, 2015. details

  18. Aurora Ramirez and Jose Raul Romero and Sebastian Ventura. An approach for the evolutionary discovery of software architectures. Information Sciences, 305:234-255, 2015. details

  19. J. M. Luna and C. Romero and J. R. Romero and S. Ventura. An Evolutionary Algorithm for the Discovery of Rare Class Association Rules in Learning Management Systems. Applied Intelligence, 42(3):501-513, 2015. details

  20. Juan L. Olmo and Jose R. Romero and Sebastian Ventura. Swarm-based metaheuristics in automatic programming: a survey. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 4(6):445-469, 2014. details

  21. J. M. Luna and J. R. Romero and S. Ventura. On the adaptability of G3PARM to the extraction of rare association rules. Knowledge and Information Systems, 38(2):391-418, 2014. details

  22. Juan Luis Olmo and Jose Raul Romero and Sebastian Ventura. Single and multi-objective ant programming for mining interesting rare association rules. International Journal of Hybrid Intelligent Systems, 11(3):197-209, 2014. details

  23. Jose Maria Luna and Jose Raul Romero and Cristobal Romero and Sebastian Ventura. Reducing gaps in quantitative association rules: A genetic programming free-parameter algorithm. Integrated Computer-Aided Engineering, 21(4):321-337, 2014. details

  24. Jose Maria Luna and Jose Raul Romero and Cristobal Romero and Sebastian Ventura. On the Use of Genetic Programming for Mining Comprehensible Rules in Subgroup Discovery. IEEE Transactions on Cybernetics, 44(12):2329-2341, 2014. details

  25. Cristobal Romero and Amelia Zafra and Jose Maria Luna and Sebastian Ventura. Association rule mining using genetic programming to provide feedback to instructors from multiple-choice quiz data. Expert Systems, 30(2):162-172, 2013. details

  26. Juan Luis Olmo and Jose Maria Luna and Jose Raul Romero and Sebastian Ventura. Mining association rules with single and multi-objective grammar guided ant programming. Integrated Computed-Aided Engineering, 20(3):217-234, 2013. details

  27. Carlos Marquez-Vera and Alberto Cano and Cristobal Romero and Sebastian Ventura. Predicting student failure at school using genetic programming and different data mining approaches with high dimensional and imbalanced data. Applied Intelligence, 38(3):315-330, 2013. details

  28. J. M. Luna and J. R. Romero and S. Ventura. Grammar-based multi-objective algorithms for mining association rules. Data \& Knowledge Engineering, 86:19-37, 2013. details

  29. Alberto Cano and Jose Maria Luna and Sebastian Ventura. High performance evaluation of evolutionary-mined association rules on GPUs. The Journal of Supercomputing, 66(3):1438-1461, 2013. details

  30. Alberto Cano and Juan Luis Olmo and Sebastian Ventura. Parallel multi-objective Ant Programming for classification using GPUs. Journal of Parallel and Distributed Computing, 73(6):713-728, 2013. details

  31. Alberto Cano and Amelia Zafra and Sebastian Ventura. An Interpretable Classification Rule Mining Algorithm. Information Sciences, 240:1-20, 2013. details

  32. Amelia Zafra and Sebastian Ventura. Multi-objective approach based on grammar-guided genetic programming for solving multiple instance problems. Soft Computing - A Fusion of Foundations, Methodologies and Applications, 16(6):955-977, 2012. details

  33. Jose Maria Luna and Jose Raul Romero and Sebastian Ventura. Design and behavior study of a grammar-guided genetic programming algorithm for mining association rules. Knowledge and Information Systems, 32(1):53-76, 2012. details

  34. Amelia Zafra and Sebastian Ventura. Multi-instance genetic programming for predicting student performance in web based educational environments. Applied Soft Computing, 12(8):2693-2706, 2012. details

  35. J. L. Olmo and J. R. Romero and S. Ventura. Classification rule mining using ant programming guided by grammar with multiple Pareto fronts. Soft Computing, 16(12):2143-2163, 2012. details

  36. Alberto Cano and Amelia Zafra and Sebastian Ventura. Speeding up the evaluation phase of GP classification algorithms on GPUs. Soft Computing - A Fusion of Foundations, Methodologies and Applications, 16(2):187-202, 2012. details

  37. Jose Luis Avila-Jimenez and Eva Lucrecia Gibaja Galindo and Amelia Zafra and Sebastian Ventura. A Gene Expression Programming Algorithm for Multi-Label Classification. Journal of Multiple-Valued Logic and Soft Computing, 17(2-3):183-206, 2011. details

  38. Amelia Zafra and Eva L. Gibaja and Sebastian Ventura. Multiple Instance Learning with Multiple Objective Genetic Programming for Web Mining. Applied Soft Computing, 11(1):93-102, 2011. details

  39. Juan Luis Olmo and Jose Raul Romero and Sebastian Ventura. Using Ant Programming Guided by Grammar for Building Rule-Based Classifiers. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 41(6):1585-1599, 2011. details

  40. Amelia Zafra and Sebastian Ventura. G3P-MI: A genetic programming algorithm for multiple instance learning. Information Sciences, 180(23):4496-4513, 2010. details

  41. Pedro G. Espejo and Sebastian Ventura and Francisco Herrera. A Survey on the Application of Genetic Programming to Classification. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 40(2):121-144, 2010. details

  42. A. Zafra and C. Romero and S. Ventura and E. Herrera-Viedma. Multi-instance genetic programming for web index recommendation. Expert Systems with Applications, 36(9):11470-11479, 2009. details

  43. Sebastian Ventura and Cristobal Romero and Amelia Zafra and Jose A. Delgado and Cesar Hervas. JCLEC: a Java framework for evolutionary computation. Soft Computing - A Fusion of Foundations, Methodologies and Applications, 12(4):381-392, 2008. details

  44. Pedro G. Espejo and Cesar Hervas and Sebastian Ventura and Cristobal Romero. Eleccion de Operadores Logicos para la Induccion de Conocimiento Comprensible. Inteligencia Artificial, Revista Iberoamericana de Inteligencia Artificial, 29:19-30, 2006. Ejemplar dedicado a: Mineria de Datos. details

  45. Cristobal Romero and Sebastian Ventura and Paul De Bra. Knowledge Discovery with Genetic Programming for Providing Feedback to Courseware Authors. User Modeling and User-Adapted Interaction, 14(5):425-464, 2004. details

Genetic Programming Books by Sebastian Ventura

Genetic Programming conference papers by Sebastian Ventura

  1. Jose A. Delgado-Osuna and Carlos Garcia-Martinez and Sebastian Ventura. Smart Operators for Inducing Colorectal Cancer Classification Trees with PonyGE2 Grammatical Evolution Python Package. In Carlos A. Coello Coello and Sanaz Mostaghim editors, 2022 IEEE Congress on Evolutionary Computation (CEC), Padua, Italy, 2022. details

  2. Rafael Barbudo and Sebastian Ventura and Jose Raul Romero. Grammar-Based Evolutionary Approach for Automatic Workflow Composition with Open Preprocessing Sequence. In Ajith Abraham and Andries Engelbrecht and Fabio Scotti and Niketa Gandhi and Pooja Manghirmalani Mishra and Giancarlo Fortino and Virgilijus Sakalauskas and Sabri Pllana editors, Proceedings of the 13th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2021), volume 417, pages 647-656, 2021. Springer. details

  3. Jose M. Moyano and Eva L. Gibaja and Krzysztof J. Cios and Sebastian Ventura. Tree-Shaped Ensemble of Multi-Label Classifiers using Grammar-Guided Genetic Programming. In Yaochu Jin editor, 2020 IEEE Congress on Evolutionary Computation, CEC 2020, page paper id24049, internet, 2020. IEEE Press. details

  4. Jose Maria Luna and Francisco Padillo and Sebastian Ventura. Associative classification in big data through a G3P approach. In Proceedings of the 4th International Conference on Internet of Things, Big Data and Security - IoTBDS, pages 94-102, Heraklion, Crete, Greece, 2019. SciTePress. details

  5. Oscar Gabriel Reyes Pupo and Jose Maria Moyano Murillo and Jose Maria Luna and Sebastian Ventura. A gene expression programming method for multi-target regression. In Saaid Amzazi and Abdellatif El Afia and Mohammed Essaaidi editors, Proceedings of the International Conference on Learning and Optimization Algorithms: Theory and Applications, LOPAL 2018, Rabat, Morocco, May 2-5, 2018, pages 2:1-2:6, 2018. ACM. details

  6. Carlos Garcia-Martinez and Sebastian Ventura. Multi-view semi-supervised learning using genetic programming interpretable classification rules. In Jose A. Lozano editor, 2017 IEEE Congress on Evolutionary Computation (CEC), pages 573-579, Donostia, San Sebastian, Spain, 2017. IEEE. details

  7. Francisco Padillo and Jose Maria Luna and Sebastian Ventura. An evolutionary algorithm for mining rare association rules: A Big Data approach. In Jose A. Lozano editor, Proceedings of the 2017 IEEE Congress on Evolutionary Computation, pages 2007-2014, Donostia, San Sebastian, Spain, 2017. IEEE. details

  8. David Pinheiro and Alberto Cano and Sebastian Ventura. Synthesis of In-Place Iterative Sorting Algorithms Using GP: A Comparison Between STGP, SFGP, G3P and GE. In Francisco Pereira and Penousal Machado and Ernesto Costa and Amilcar Cardoso editors, 17th Portuguese Conference on Artificial Intelligence, volume 9273, pages 305-310, 2015. Springer. details

  9. Alberto Cano and Sebastian Ventura. GPU-parallel subtree interpreter for genetic programming. In Christian Igel and Dirk V. Arnold and Christian Gagne and Elena Popovici and Anne Auger and Jaume Bacardit and Dimo Brockhoff and Stefano Cagnoni and Kalyanmoy Deb and Benjamin Doerr and James Foster and Tobias Glasmachers and Emma Hart and Malcolm I. Heywood and Hitoshi Iba and Christian Jacob and Thomas Jansen and Yaochu Jin and Marouane Kessentini and Joshua D. Knowles and William B. Langdon and Pedro Larranaga and Sean Luke and Gabriel Luque and John A. W. McCall and Marco A. Montes de Oca and Alison Motsinger-Reif and Yew Soon Ong and Michael Palmer and Konstantinos E. Parsopoulos and Guenther Raidl and Sebastian Risi and Guenther Ruhe and Tom Schaul and Thomas Schmickl and Bernhard Sendhoff and Kenneth O. Stanley and Thomas Stuetzle and Dirk Thierens and Julian Togelius and Carsten Witt and Christine Zarges editors, GECCO '14: Proceedings of the 2014 conference on Genetic and evolutionary computation, pages 887-894, Vancouver, BC, Canada, 2014. ACM. details

  10. Jose M. Luna and Jose R. Romero and Cristobal Romero and Sebastian Ventura. Discovering Subgroups by Means of Genetic Programming. In Krzysztof Krawiec and Alberto Moraglio and Ting Hu and A. Sima Uyar and Bin Hu editors, Proceedings of the 16th European Conference on Genetic Programming, EuroGP 2013, volume 7831, pages 121-132, Vienna, Austria, 2013. Springer Verlag. details

  11. Alberto Cano and Amelia Zafra and Eva L. Gibaja and Sebastian Ventura. A Grammar-Guided Genetic Programming Algorithm for Multi-Label Classification. In Krzysztof Krawiec and Alberto Moraglio and Ting Hu and A. Sima Uyar and Bin Hu editors, Proceedings of the 16th European Conference on Genetic Programming, EuroGP 2013, volume 7831, pages 217-228, Vienna, Austria, 2013. Springer Verlag. details

  12. Juan Luis Olmo Ortiz and Jose-Raul Romero and Sebastian Ventura. On the Use of Ant Programming for Mining Rare Association Rules. In Simone Ludwig and Patricia Melin and Ajith Abraham and Ana Maria Madureira and Kendall Nygard and Oscar Castillo and Azah Kamilah Muda and Kun Ma and Emilio Corchado editors, 5th World Congress on Nature and Biologically Inspired Computing, pages 220-225, Fargo, USA, 2013. IEEE. details

  13. Juan Luis Olmo and Jose Raul Romero and Sebastian Ventura. Multi-objective Ant Programming for Mining Classification Rules. In Alberto Moraglio and Sara Silva and Krzysztof Krawiec and Penousal Machado and Carlos Cotta editors, Proceedings of the 15th European Conference on Genetic Programming, EuroGP 2012, volume 7244, pages 146-157, Malaga, Spain, 2012. Springer Verlag. details

  14. Juan Luis Olmo and Alberto Cano and Jose Raul Romero and Sebastian Ventura. Binary and multiclass imbalanced classification using multi-objective ant programming. In 12th International Conference on Intelligent Systems Design and Applications (ISDA 2012), pages 70-76, 2012. details

  15. Jose Maria Luna and Jose Raul Romero and Cristobal Romero and Sebastian Ventura. A genetic programming free-parameter algorithm for mining association rules. In 12th International Conference on Intelligent Systems Design and Applications (ISDA 2012), pages 64-69, 2012. details

  16. Alberto Cano and Amelia Zafra and Sebastian Ventura. A Parallel Genetic Programming Algorithm for Classification. In Emilio Corchado and Marek Kurzynski and Michal Wozniak editors, Proceedings of the 6th International Conference on Hybrid Artificial Intelligent Systems (HAIS 2011) Part I, volume 6678, pages 172-181, Wroclaw, Poland, 2011. Springer. details

  17. Juan Luis Olmo and Jose Maria Luna and Jose Raul Romero and Sebastian Ventura. Association rule mining using a multi-objective grammar-based ant programming algorithm. In 11th International Conference on Intelligent Systems Design and Applications (ISDA 2011), pages 971-977, Cordoba, 2011. details

  18. Jose Maria Luna and Jose Raul Romero and Sebastian Ventura. Mining and representing rare association rules through the use of genetic programming. In Third World Congress on Nature and Biologically Inspired Computing (NaBIC 2011), pages 86-91, Salamanca, 2011. details

  19. Amelia Zafra and Sebastian Ventura. Grammar guided genetic programming for multiple instance learning: an experimental study. In Juergen Branke and Martin Pelikan and Enrique Alba and Dirk V. Arnold and Josh Bongard and Anthony Brabazon and Juergen Branke and Martin V. Butz and Jeff Clune and Myra Cohen and Kalyanmoy Deb and Andries P Engelbrecht and Natalio Krasnogor and Julian F. Miller and Michael O'Neill and Kumara Sastry and Dirk Thierens and Jano van Hemert and Leonardo Vanneschi and Carsten Witt editors, GECCO '10: Proceedings of the 12th annual conference on Genetic and evolutionary computation, pages 909-916, Portland, Oregon, USA, 2010. ACM. details

  20. Juan Luis Olmo and Jose Raul Romero and Sebastian Ventura. A grammar based Ant Programming algorithm for mining classification rules. In IEEE Congress on Evolutionary Computation (CEC 2010), Barcelona, Spain, 2010. IEEE Press. details

  21. Jose Maria Luna and Jose Raul Romero and Sebastian Ventura. G3PARM: A Grammar Guided Genetic Programming algorithm for mining association rules. In IEEE Congress on Evolutionary Computation (CEC 2010), Barcelona, Spain, 2010. IEEE Press. details

  22. Jose Maria Luna and Aurora Ramirez and Jose Raul Romero and Sebastian Ventura. An intruder detection approach based on infrequent rating pattern mining. In 10th International Conference on Intelligent Systems Design and Applications (ISDA 2010), pages 682-688, 2010. details

  23. J. M. Luna and J. R. Romero and S. Ventura. Analysis of the Effectiveness of G3PARM Algorithm. In Emilio Corchado and Manuel Grana Romay and Alexandre Manhaes Savio editors, Proceedings of the 5th International Conference on Hybrid Artificial Intelligence Systems (HAIS 2010) Part II, volume 6077, pages 27-34, San Sebastian, Spain, 2010. Springer. details

  24. Alberto Cano and Amelia Zafra and Sebastian Ventura. Solving Classification Problems Using Genetic Programming Algorithms on GPUs. In Emilio Corchado and Manuel Grana Romay and Alexandre Manhaes Savio editors, Hybrid Artificial Intelligence Systems, volume 6077, pages 17-26, San Sebastian, Spain, 2010. Springer. details

  25. Amelia Zafra and Sebastian Ventura. A Comparison of Multi-objective Grammar-Guided Genetic Programming Methods to Multiple Instance Learning. In Emilio Corchado and Xindong Wu and Erkki Oja and \'Alvaro Herrero and Bruno Baruque editors, Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2009, volume 5572, pages 450-458, Salamanca, Spain, 2009. Springer. details

  26. J. L. Avila and Eva Lucrecia Gibaja Galindo and Sebastian Ventura. Multi-label Classification with Gene Expression Programming. In Emilio Corchado and Xindong Wu and Erkki Oja and Alvaro Herrero and Bruno Baruque editors, Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2009, volume 5572, pages 629-637, Salamanca, Spain, 2009. Springer. details

  27. Amelia Zafra and Sebastian Ventura. Predicting Student Grades in Learning Management Systems with Multiple Instance Learning Genetic Programming. In Tiffany Barnes and Michel C. Desmarais and Crist\'obal Romero and Sebasti\'an Ventura editors, Educational Data Mining - EDM 2009, Cordoba, Spain, July 1-3, 2009. Proceedings of the 2nd International Conference on Educational Data Mining, pages 309-318, 2009. http://www.educationaldatamining.org. details

  28. Amelia Zafra and Cristobal Romero and Sebastian Ventura. Predicting Academic Achievement Using Multiple Instance Genetic Programming. In Ninth International Conference on Intelligent Systems Design and Applications, ISDA '09, pages 1120-1125, 2009. details

  29. Amelia Zafra and Sebastian Ventura. Modelling User Preferences with Multi-Instance Genetic Programming. In Luis Magdalena and Jose Luis Verdegay editors, Information processing and Management of Uncertainty in Knowledge based systems, IPMU 20018, Malaga, Spain, 2008. details

  30. Amelia Zafra and Eva Gibaja and Sebastian Ventura. Multiple Instance Learning with MultiObjective Genetic Programming for Web Mining. In Eighth International Conference on Hybrid Intelligent Systems, HIS '08, pages 513-518, 2008. details

  31. Amelia Zafra and Sebastian Ventura and Enrique Herrera-Viedma and Cristobal Romero. Multiple Instance Learning with Genetic Programming for Web Mining. In Francisco Sandoval Hern\'andez and Alberto Prieto and Joan Cabestany and Manuel Gra\~na editors, Proceedings of the 9th International Work-Conference on Artificial Neural Networks, IWANN 2007, volume 4507, pages 919-927, San Sebasti\'an, Spain, 2007. Springer. details

  32. Amelia Zafra and Sebastian Ventura. Multi-objective Genetic Programming for Multiple Instance Learning. In Joost N. Kok and Jacek Koronacki and Ramon L\'opez de M\'antaras and Stan Matwin and Dunja Mladenic and Andrzej Skowron editors, 18th European Conference on Machine Learning, ECML 2007, volume 4701, pages 790-797, Warsaw, Poland, 2007. Springer. details

Genetic Programming book chapters by Sebastian Ventura

  1. Sebastian Ventura and Jose Maria Luna. Genetic Programming in Pattern Mining. In Pattern Mining with Evolutionary Algorithms, chapter 5, pages 87-117. Springer, 2016. details

  2. J. M. Luna and A. Cano and S. Ventura. Genetic Programming for Mining Association Rules in Relational Database Environments. In Amir H. Gandomi and Amir H. Alavi and Conor Ryan editors, Handbook of Genetic Programming Applications, chapter 17, pages 431-450. Springer, 2015. details

  3. Amelia Zafra and Cristobal Romero and Sebastian Ventura. Multi-Instance Learning versus Single-Instance Learning for Predicting the Student's Performance. In Cristobal Romero and Sebastian Ventura and Mykola Pechenizkiy and Ryan S. J. D. Baker editors, Handbook of Educational Data Mining, chapter 13, pages 187-200. CRC Press, 2010. details

  4. Juan Luis Olmo and Jose Maria Luna and Jose Raul Romero and Sebastian Ventura. An Automatic Programming ACO-Based Algorithm for Classification Rule Mining. In Yves Demazeau and Frank Dignum and Juan M. Corchado and Javier Bajo and Rafael Corchuelo and Emilio Corchado and Florentino Fernandez-Riverola and Vicente J. Julian and Pawel Pawlewski and Andrew Campbell editors, Trends in Practical Applications of Agents and Multiagent Systems, volume 71 of Advances in Intelligent and Soft Computing, pages 649-656. Springer, 2010. details

  5. Jose Luis Avila-Jimenez and Eva Gibaja and Sebastian Ventura. Evolving Multi-label Classification Rules with Gene Expression Programming: A Preliminary Study. In Emilio Corchado and Manuel Grana Romay and Alexandre Manhaes Savio editors, Hybrid Artificial Intelligence Systems, volume 6077 of Lecture Notes in Computer Science, pages 9-16. Springer, San Sebastian, Spain, 2010. details

  6. C. Romero and S. Ventura and C. Hervas and P. Gonzalez. Rule mining with GBGP to improve web-based adaptive educational systems. In C. Romero Morales and S. Ventura editors, Data mining in e-learning, volume 4 of Advances in Management Information, pages 171-188. WitPress, 2006. details

  7. C. Romero and S. Ventura and C. Hervas and P. Gonzalez. Rule discovery in Web-based educational systems using Grammar-Based Genetic Programming. In A. Zanasi and C. A. Brebbia and N. Ebecken editors, Data Mining VI: Data Mining, Text Mining and their Business Applications, volume 35 of Information and Communication Technologies, pages 113-126. WitPress, 2005. details