Publications Listing
Filter Publications:
Complementary Material for Selected Papers
Number of Results: 62
Jump to Year: In Press, 2020, 2019, 2018, 2017, 2016, 2015, 2014, 2013, 2012, 2011, 2010, 2009, 2008
In Press (2)
- [2573] A. Valdivia, E. Martínez-Cámara, I. Chaturvedi, M.V. Luzón, E. Cambria, Y. Ong, F. Herrera. What do people think about this monument? Understanding negative reviews via deep learning, clustering and descriptive rules. Journal of Ambient Intelligence and Humanized Computing (2018), in press. doi: 10.1007/s12652-018-1150-3
Read the paper - [2597] F.J. Baldán, J.M. Benítez. Distributed FastShapelet Transform: a Big Data time series classification algorithm. Information Sciences, Accepted, in press. doi: 10.1016/j.ins.2018.10.028
COMPLEMENTARY MATERIAL to the paper: datasets, experimental results and source codes
2020 (1)
- [2742] J.A. Moral-Muñoz, E. Herrera-Viedma, A. Santisteban-Espejo, M.J. Cobo. Software tools for conducting bibliometric analysis in science: An up-to-date review. Profesional de la información, 29:1, e290103. (2020). doi: 10.3145/epi.2020.ene.03
Link to PDF
2019 (2)
- [2568] A. Castillo, S. Tabik, F. Pérez, R. Olmos, F. Herrera. Brightness guided preprocessing for automatic cold steel weapon detection in surveillance videos with deep learning. Neurocomputing 330(2019) 151-161. doi: 10.1016/j.neucom.2018.10.076
Complementary material - [2575] M. López, A. Valdivia, E. Martínez-Cámara, M.V. Luzón, F. Herrera. E2SAM: Evolutionary Ensemble of Sentiment Analysis Methods for Domain Adaptation. Information Sciences, 480 (2019) 273-286. doi: 10.1016/j.ins.2018.12.038
Read the paper
2018 (7)
- [2279] F.J. Baldán, S.Ramirez-Gallego, C.Bergmeir, F.Herrera, J.M.Benitez-Sanchez. A Forecasting Methodology for Workload Forecasting in Cloud Systems. IEEE Transactions on Cloud Computing 6:4 (2018) 929-941. doi: 10.1109/TCC.2016.2586064
COMPLEMENTARY MATERIAL to the paper - [2339] R. Rekik, I. Kallel, J. Casillas, A.M. Alimi. Assessing web sites quality: a systematic literature review by text and association rules mining. International Journal of Information Management 38:1 (2018) 201-216. doi: 10.1016/j.ijinfomgt.2017.06.007
PDF - [2383] J. Luengo, S.O. Shim, S. Alshomrani, A. Altalhi, F. Herrera. CNC-NOS: Class Noise Cleaning by Ensemble Filtering and Noise Scoring. Knowledge-Based Systems 140 (2018) 27-49. doi: 10.1016/j.knosys.2017.10.026
OMPLEMENTARY MATERIAL to the paper: datasets, experimental results 
[2611] S. Ramírez-Gallego. Distributed data reduction algorithms for Big Data. Department of Computer Science and Artificial Intelligence, University of Granada.
Advisor: F. Herrera, S. García
Bibliography information
[2613] Cascón-Katchadourian, J.. Documentación histórica gráfica granadina. Aplicación de herramientas SIG para mejorar su recuperación: georreferenciación y geolocalización. Department of Computer Science and Artificial Intelligence, University of Granada.
Advisor: E. Herrera-Viedma, A. A. Ruíz
Bibliography information- [2618] N. Rodríguez Barroso, E. Martínez-Cámara, F. Herrera. SCI2S at TASS 2018: Emotion Classification with Recurrent Neural Networks. In Proceedings of TASS 2018: Workshop on Semantic Analysis at SEPLN (TASS 2018) co-located with 34nd SEPLN Conference (SEPLN 2018), 2172 (2018) 117-123. ISSN: 1613-0073.
Read the paper - [2619] A. Valdivia, E. Martínez-Cámara, M.V. Luzón, F. Herrera. Resumiendo Opiniones Negativas con Deep Learning y Reglas Descriptivas. In I Workshop en Ciencia de Datos en Redes Sociales (CIDRES 2018) co-located in XVIII Conferencia de la Asociación Española en Inteligencia Artificial (CAEPIA 2018), 1017-1022. Granada (Spain), October 2018.
Read the paper
2017 (2)
- [2133] S. García, S. Ramírez-Gallego, J. Luengo, F. Herrera. Big Data: Preprocesamiento y calidad de datos. Novática (Revista de la Asociación de Técnicos de Informática), Monografía Big Data, 237 (2017) 17-23..
Enlace a la revista completa 
[2614] P.D. Gutiérrez. Identificación y clasificación biométrica a gran escala basada en huellas dactilares y GPU. Department of Computer Science and Artificial Intelligence, University of Granada.
Advisor: F. Herrera, M. Lastra
Bibliography information
2016 (7)
- [1920] J. Alcalá-Fdez, J.M. Alonso. A Survey of Fuzzy Systems Software: Taxonomy, Current Research Trends and Prospects. IEEE Transactions on Fuzzy Systems 24:1 (2016) 40-56. doi: 10.1109/TFUZZ.2015.2426212
COMPLEMENTARY MATERIAL to the paper: software, bibliography, events, etc - [2079] D. Martin, J. Alcalá-Fdez, A. Rosete, F. Herrera. NICGAR: a Niching Genetic Algorithm to Mine a Diverse Set of Interesting Quantitative Association Rules. Information Sciences 355-356 (2016) 208-228. doi: 10.1016/j.ins.2016.03.039
COMPLEMENTARY MATERIAL to the paper: datasets, experimental results, etc - [1975] R. Yera, J. Castro, L. Martínez. A fuzzy model for managing natural noise in recommender systems. Applied Soft Computing 40 (2016) 187-198. doi: 10.1016/j.asoc.2015.10.060
source code of the experimentation - [2014] S. García, J. Luengo, F. Herrera. Tutorial on practical tips of the most influential data preprocessing algorithms in data mining. Knowledge-Based Systems 98 (2016) 1–29. doi: 10.1016/j.knosys.2015.12.006
COMPLEMENTARY MATERIAL to the paper: datasets, experimental results and source codes - [2252] P.D. Gutiérrez, M. Lastra, J. Bacardit, J.M. Benítez, F. Herrera. GPU-SME-kNN: Scalable and memory efficient kNN and lazy learning using GPUs. Information Sciences 373, 165-182. doi: 10.1016/j.ins.2016.08.089
COMPLEMENTARY MATERIAL to the paper: experimental results and source codes - [2342] R. Rekik, I. Kallel, J. Casillas, A.M. Alimi. Using multiple criteria decision making approaches to assess the quality of web sites. International Journal of Computer Science and Information Security 14:7 (2016) 747-761.
paper link - [2353] C. Bergmeir, D. Molina, J.M. Benitez. Memetic algorithms with local search chains in R: The Rmalschains package. Journal of Statistical Software. 75:1 (2016) 1-33.. doi: 10.18637/jss.v075.i04
R source code of the package, replication code from the manuscript
2015 (7)
- [1683] I. Triguero, S. García, F. Herrera. Self-Labeled Techniques for Semi-Supervised Learning: Taxonomy, Software and Empirical Study. Knowledge and Information Systems 42 (2015) 245-284. doi: 10.1007/s10115-013-0706-y
COMPLEMENTARY MATERIAL to the paper: datasets, experimental results and source codes - [1824] José A. Sáez, J. Luengo, Jerzy Stefanowski, F. Herrera. SMOTE–IPF: Addressing the noisy and borderline examples problem in imbalanced classification by a re-sampling method with filtering. Information Sciences 291 (2015) 184-203. doi: 10.1016/j.ins.2014.08.051
COMPLEMENTARY MATERIAL to the paper - [1891] M. Galar, J. Derrac, D. Peralta, I. Triguero, D. Paternain, C. Lopez-Molina, S. García, J.M. Benítez, M. Pagola, E. Barrenechea, H. Bustince, F. Herrera. A Survey of Fingerprint Classification Part II: Experimental Analysis and Ensemble Proposal. Knowledge-Based Systems 81 (2015) 98-116. doi: 10.1016/j.knosys.2015.02.015
COMPLEMENTARY MATERIAL to the paper: datasets, experimental results and source codes - [1921] D. Peralta, M. Galar, I. Triguero, D. Paternain, S. García, E. Barrenechea, J. M. Benítez, H. Bustince, F. Herrera. A Survey on Fingerprint Minutiae-based Local Matching for Verification and Identification: Taxonomy and Experimental Evaluation. Information Sciences 315 (2015) 67-87. doi: 10.1016/j.ins.2015.04.013
COMPLEMENTARY MATERIAL to the paper: experimental results and statistical tests - [1979] L.J. Morales Chacón, M.J. Cobo. Usabilidad de los sitios web de Centros de Formación Profesional de la Región de Murcia. No Solo Usabilidad, nº 14 (2015). nosolousabilidad.com. ISSN 1886-8592.
URL to article 
[2615] B. Lacroix. Region-based memetic algorithms for global and multimodal continuous optimisation. Department of Computer Science and Artificial Intelligence, University of Granada.
Advisor: D. Molina and F. Herrera
Bibliography information
[2617] L. S. Riza. Data science and Big Data Processing in R: representations and software. Department of Computer Science and Artificial Intelligence, University of Granada.
Advisor: J.M. Benítez and F. Herrera
Bibliography information
2014 (6)
- [1698] J. Derrac, S. García, F. Herrera. Fuzzy Nearest Neighbor Algorithms: Taxonomy, Experimental analysis and Prospects . Information Sciences 260 (2014) 98-119. doi: 10.1016/j.ins.2013.10.038
COMPLEMENTARY MATERIAL to the paper: datasets, experimental results and source codes - [1557] José A. Sáez, M. Galar, J. Luengo, F. Herrera. Analyzing the Presence of Noise in Multi-class Problems: Alleviating its Influence with the One-vs-One Decomposition. Knowledge and Information Systems 38:1 (2014) 179-206. doi: 10.1007/s10115-012-0570-1
COMPLEMENTARY MATERIAL to the paper - [1670] D. Peralta, I. Triguero, R. Sanchez-Reillo, F. Herrera, J.M. Benítez. Fast Fingerprint Identification for Large Databases. Pattern Recognition 47:2 (2014) 588–602. doi: 10.1016/j.patcog.2013.08.002
COMPLEMENTARY MATERIAL to the paper: datasets, experimental results and source codes - [1742] S. Río, V. López, J.M. Benítez, F. Herrera. On the use of MapReduce for Imbalanced Big Data using Random Forest. Information Sciences 285 (2014) 112-137. doi: 10.1016/j.ins.2014.03.043
COMPLEMENTARY MATERIAL to the paper - [1791] José A. Sáez, J. Derrac, J. Luengo, F. Herrera. Statistical computation of feature weighting schemes through data estimation for nearest neighbor classifiers. Pattern Recognition 47:12 (2014) 3941–3948. doi: 10.1016/j.patcog.2014.06.012
COMPLEMENTARY MATERIAL to the paper - [1794] J. Derrac, S. García, S. Hui, P. N. Suganthan, F. Herrera. Analyzing convergence performance of evolutionary algorithms: A statistical approach. Information Sciences 289 (2014) 41-58. doi: 10.1016/j.ins.2014.06.009
COMPLEMENTARY MATERIAL to the paper
2013 (5)
- [1469] S. García, J. Luengo, José A. Sáez, V. López, F. Herrera. A Survey of Discretization Techniques: Taxonomy and Empirical Analysis in Supervised Learning. IEEE Transactions on Knowledge and Data Engineering 25:4 (2013) 734-750. doi: 10.1109/TKDE.2012.35
COMPLEMENTARY MATERIAL to the paper - [1539] José A. Sáez, J. Luengo, F. Herrera. Predicting Noise Filtering Efficacy with Data Complexity Measures for Nearest Neighbor Classification. Pattern Recognition 46:1 (2013) 355-364. doi: 10.1016/j.patcog.2012.07.009
COMPLEMENTARY MATERIAL to the paper - [1521] M. Fazzolari, R. Alcalá, Y. Nojima, H. Ishibuchi, F. Herrera. A Review of the Application of Multi-Objective Evolutionary Fuzzy Systems: Current Status and Further Directions. IEEE Transactions on Fuzzy Systems, 21:1 (2013) 45-65.
COMPLEMENTARY MATERIAL to the paper: links to the papers with doi, new contributions, etc - [1655] José A. Sáez, M. Galar, J. Luengo, F. Herrera. Tackling the Problem of Classification with Noisy Data using Multiple Classifier Systems:Analysis of the Performance and Robustness. Information Sciences 247 (2013) 1-20. doi: 10.1016/j.ins.2013.06.002
COMPLEMENTARY MATERIAL to the paper - [1657] V. López, A. Fernandez, S. García, V. Palade, F. Herrera. An Insight into Classification with Imbalanced Data: Empirical Results and Current Trends on Using Data Intrinsic Characteristics. Information Sciences 250 (2013) 113-141. doi: 10.1016/j.ins.2013.07.007
COMPLEMENTARY MATERIAL to the paper
2012 (5)
- [1365] I. Triguero, J. Derrac, S. García, F. Herrera. A Taxonomy and Experimental Study on Prototype Generation for Nearest Neighbor Classification. IEEE Transactions on Systems, Man, and Cybernetics--Part C: Applications and Reviews 42 (1) (2012) 86-100. doi: 10.1109/TSMCC.2010.2103939
COMPLEMENTARY MATERIAL to the paper: datasets, experimental results and source codes - [1408] J. Luengo, S. García, F. Herrera. On the choice of the best imputation methods for missing values considering three groups of classification methods. Knowledge and Information Systems 32:1 (2012) 77-108. doi: 10.1007/s10115-011-0424-2
COMPLEMENTARY MATERIAL to the paper: Software, data sets, results and methods description - [1409] S. García, J. Derrac, J.R. Cano, F. Herrera. Prototype Selection for Nearest Neighbor Classification: Taxonomy and Empirical Study. IEEE Transactions on Pattern Analysis and Machine Intelligence 34:3 (2012) 417-435. doi: 10.1109/TPAMI.2011.142
COMPLEMENTARY MATERIAL to the paper: datasets, experimental results and source codes - [1514] J. Derrac, I. Triguero, S. García, F. Herrera. Integrating Instance Selection, Instance Weighting and Feature Weighting for Nearest Neighbor Classifiers by Co-evolutionary Algorithms. IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics 42:5 (2012) 1383-1397. doi: 10.1109/TSMCB.2012.2191953
COMPLEMENTARY MATERIAL to the paper: datasets, experimental results and source codes - [1538] J. G. Moreno-Torres, José A. Sáez, F. Herrera. Study on the Impact of Partition-Induced Dataset Shift on k-fold Cross-Validation. IEEE Transactions on Neural Networks and Learning Systems 23:8 (2012) 1304-1312. doi: 10.1109/TNNLS.2012.2199516
COMPLEMENTARY MATERIAL to the paper
2011 (5)
- [1277] J. Alcalá-Fdez, A. Fernandez, J. Luengo, J. Derrac, S. García, L. Sánchez, F. Herrera. KEEL Data-Mining Software Tool: Data Set Repository, Integration of Algorithms and Experimental Analysis Framework. Journal of Multiple-Valued Logic and Soft Computing 17:2-3 (2011) 255-287.
SOFTWARE associated to the paper here - [1371] M. Galar, A. Fernandez, E. Barrenechea, H. Bustince, F. Herrera. An Overview of Ensemble Methods for Binary Classifiers in Multi-class Problems: Experimental Study on One-vs-One and One-vs-All Schemes. Pattern Recognition 44:8 (2011) 1761-1776. doi: 10.1016/j.patcog.2011.01.017
COMPLEMENTARY MATERIAL to the paper: dataset partitions, results, figures, etc - [1374] J. Derrac, S. García, D. Molina, F. Herrera. A Practical Tutorial on the Use of Nonparametric Statistical Tests as a Methodology for Comparing Evolutionary and Swarm Intelligence Algorithms. Swarm and Evolutionary Computation 1:1 (2011) 3-18. doi: 10.1016/j.swevo.2011.02.002
COMPLEMENTARY MATERIAL to the paper: Software and tests description - [1380] R. Alcalá, M.J. Gacto, F. Herrera. A Fast and Scalable Multi-Objective Genetic Fuzzy System for Linguistic Fuzzy Modeling in High-Dimensional Regression Problems. IEEE Transactions on Fuzzy Systems 19:4 (2011) 666-681. doi: 10.1109/TFUZZ.2011.2131657
COMPLEMENTARY MATERIAL to the paper: dataset partitions, results, figures, etc - [1383] M.J. Gacto, R. Alcalá, F. Herrera. Interpretability of Linguistic Fuzzy Rule-Based Systems: An Overview of Interpretability Measures. Information Sciences, 181:20 (2011) 4340–4360.
COMPLEMENTARY MATERIAL to the paper: links to the papers with doi, new contributions, etc
2010 (6)
- [1104] A. Fernandez, S. García, J. Luengo, E. Bernadó-Mansilla, F. Herrera. Genetics-Based Machine Learning for Rule Induction: State of the Art, Taxonomy and Comparative Study. IEEE Transactions on Evolutionary Computation 14:6 (2010) 913-941. doi: 10.1109/TEVC.2009.2039140
COMPLEMENTARY MATERIAL to the paper: dataset partitions, results, figures, etc - [1112] J. Luengo, S. García, F. Herrera. A Study on the Use of Imputation Methods for Experimentation with Radial Basis Function Network Classifiers Handling Missing Attribute Values: The good synergy between RBFs and EventCovering method. Neural Networks 23 406-418. doi: 10.1016/j.neunet.2009.11.014
COMPLEMENTARY MATERIAL to the paper: dataset partitions, results, figures, etc - [1206] S. García, A. Fernandez, J. Luengo, F. Herrera. Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental Analysis of Power. Information Sciences 180 (2010) 2044–2064. doi: 10.1016/j.ins.2009.12.010
COMPLEMENTARY MATERIAL to the paper: Software and tests description - [1227] A. Fernandez, M.J. del Jesus, F. Herrera. On the 2-Tuples Based Genetic Tuning Performance for Fuzzy Rule Based Classification Systems in Imbalanced Data-Sets. Information Sciences 180:8 (2010) 1268-1291. doi: 10.1016/j.ins.2009.12.014
COMPLEMENTARY MATERIAL to the paper here: dataset partitions, results, figures, etc - [1259] S. Alonso, F.J. Cabrerizo, E. Herrera-Viedma, F. Herrera. WoS Query Partitioner: A tool to retrieve very large numbers of items from the Web of Science using different source based partitioning approaches. Journal of the American Society for Information Science and Technology 61:8 (2010) 1582-1597. doi: 10.1002/asi.21360
SOFTWARE associated to the paper - [1316] I. Triguero, S. García, F. Herrera. IPADE: Iterative Prototype Adjustment for Nearest Neighbor Classification. IEEE Transactions on Neural Networks 21 (12) (2010) 1984-1990. doi: 10.1109/TNN.2010.2087415
COMPLEMENTARY MATERIAL to the paper: datasets, experimental results and source codes
2009 (6)
- [0758] J. Alcalá-Fdez, L. Sánchez, S. García, M.J. del Jesus, S. Ventura, J.M. Garrell, J. Otero, C. Romero, J. Bacardit, V.M. Rivas, J.C. Fernández, F. Herrera. KEEL: A Software Tool to Assess Evolutionary Algorithms for Data Mining Problems. Soft Computing 13:3 (2009) 307-318. doi: 10.1007/s00500-008-0323-y
SOFTWARE associated to the paper - [0834] S. García, D. Molina, M. Lozano, F. Herrera. A Study on the Use of Non-Parametric Tests for Analyzing the Evolutionary Algorithms' Behaviour: A Case Study on the CEC'2005 Special Session on Real Parameter Optimization. Journal of Heuristics 15 (2009) 617-644. doi: 10.1007/s10732-008-9080-4
COMPLEMENTARY MATERIAL to the paper: Software and tests description - [0893] J. Luengo, S. García, F. Herrera. A Study on the Use of Statistical Tests for Experimentation with Neural Networks: Analysis of Parametric Test Conditions and Non-Parametric Tests. Expert Systems with Applications 36 (2009) 7798-7808. doi: 10.1016/j.eswa.2008.11.041
COMPLEMENTARY MATERIAL to the paper: Software and tests description - [0896] A. Fernandez, M.J. del Jesus, F. Herrera. Hierarchical Fuzzy Rule Based Classification Systems with Genetic Rule Selection for Imbalanced Data-Sets. International Journal of Approximate Reasoning 50 (2009) 561-577. doi: 10.1016/j.ijar.2008.11.004
COMPLEMENTARY MATERIAL to the paper: dataset partitions, results, figures, etc - [0898] S. García, A. Fernandez, J. Luengo, F. Herrera. A Study of Statistical Techniques and Performance Measures for Genetics-Based Machine Learning: Accuracy and Interpretability. Soft Computing 13:10 (2009) 959-977. doi: 10.1007/s00500-008-0392-y
COMPLEMENTARY MATERIAL to the paper: Software and tests description - [0902] E. Herrera-Viedma, A.G. López-Herrera, S. Alonso, J.M. Moreno, F.J. Cabrerizo, C. Porcel. A Computer-Supported Learning System to Help Teachers to Teach Fuzzy Information Retrieval Systems. Information Retrieval, 12:2 (2009) 179–200. doi: 10.1007/s10791-008-9087-3
SOFTWARE associated to the paper
2008 (1)
- [0882] S. García, F. Herrera. An Extension on "Statistical Comparisons of Classifiers over Multiple Data Sets" for all Pairwise Comparisons. Journal of Machine Learning Research 9 (2008) 2677-2694.
COMPLEMENTARY MATERIAL to the paper: Software and tests description