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ORCIDSalvador García 0001
Person information
- affiliation (PhD 2008): University of Granada, Department of Computer Science and Artificial Intelligence, Spain
- affiliation (former): University of Jaén, Department of Computer Science, Spain
Other persons with the same name
- Salvador García (aka: Salvador Garcia) — disambiguation page
- Salvador García 0002 — Austral University of Chile, Institute of Physical and Mathematical Sciences, Valdivia, Chile
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2020 – today
- 2023
[j117]Pourya Shamsolmoali
, Masoumeh Zareapoor, Swagatam Das, Salvador García, Eric Granger, Jie Yang:
GEN: Generative Equivariant Networks for Diverse Image-to-Image Translation. IEEE Trans. Cybern. 53(2): 874-886 (2023)- [i19]Germán González-Almagro, Juan-Luis Suárez, Pablo Sánchez Bermejo, José Ramón Cano, Salvador García:
Semi-supervised Clustering with Two Types of Background Knowledge: Fusing Pairwise Constraints and Monotonicity Constraints. CoRR abs/2302.14060 (2023) - [i18]Germán González-Almagro, Daniel Peralta, Eli De Poorter, José Ramón Cano, Salvador García:
Semi-Supervised Constrained Clustering: An In-Depth Overview, Ranked Taxonomy and Future Research Directions. CoRR abs/2303.00522 (2023) - 2022
- [j116]Germán González-Almagro, Juan-Luis Suárez, Julián Luengo, José Ramón Cano, Salvador García:
3SHACC: Three stages hybrid agglomerative constrained clustering. Neurocomputing 490: 441-461 (2022) - [c50]Szymon Wojciechowski, Germán González-Almagro, Salvador García, Michal Wozniak:
Adapting K-Means Algorithm for Pair-Wise Constrained Clustering of Imbalanced Data Streams. HAIS 2022: 153-163 - [c49]Germán González-Almagro, Pablo Sánchez Bermejo, Juan-Luis Suárez, José Ramón Cano, Salvador García:
Monotonic Constrained Clustering: A First Approach. IEA/AIE 2022: 725-736 - [c48]Juan-Luis Suárez, Germán González-Almagro, Salvador García, Francisco Herrera:
A Preliminary Approach for using Metric Learning in Monotonic Classification. IEA/AIE 2022: 773-784 - [i17]Alejandro Rosales-Pérez, Salvador García, Francisco Herrera:
Handling Imbalanced Classification Problems With Support Vector Machines via Evolutionary Bilevel Optimization. CoRR abs/2204.10231 (2022) - [i16]Pourya Shamsolmoali, Masoumeh Zareapoor, Swagatam Das, Eric Granger, Salvador García:
Wasserstein Embedding for Capsule Learning. CoRR abs/2209.00232 (2022) - 2021
- [j115]Ismay Pérez-Sánchez, Bárbara Cervantes, Miguel Angel Medina-Pérez, Raúl Monroy, Octavio Loyola-González, Salvador García, Francisco Herrera:
An Indexing Algorithm Based on Clustering of Minutia Cylinder Codes for Fast Latent Fingerprint Identification. IEEE Access 9: 85488-85499 (2021) - [j114]Hoang Lam Le, Dario Landa-Silva, Mikel Galar, Salvador García, Isaac Triguero:
EUSC: A clustering-based surrogate model to accelerate evolutionary undersampling in imbalanced classification. Appl. Soft Comput. 101: 107033 (2021) - [j113]Katarzyna Stapor, Pawel Ksieniewicz, Salvador García, Michal Wozniak:
How to design the fair experimental classifier evaluation. Appl. Soft Comput. 104: 107219 (2021) - [j112]Germán González-Almagro, Julián Luengo, José Ramón Cano, Salvador García:
Enhancing instance-level constrained clustering through differential evolution. Appl. Soft Comput. 108: 107435 (2021) - [j111]Swagatam Das, Salvador García, Isaac Triguero:
Neurocomputing guest editorial for the special issue: Advances in deep and shallow machine learning approaches for handling data irregularities. Neurocomputing 419: 259-260 (2021) - [j110]Juan-Luis Suárez, Salvador García, Francisco Herrera:
A tutorial on distance metric learning: Mathematical foundations, algorithms, experimental analysis, prospects and challenges. Neurocomputing 425: 300-322 (2021) - [j109]Sergio González, Salvador García, Sheng-Tun Li, Robert Ivor John, Francisco Herrera:
Fuzzy k-nearest neighbors with monotonicity constraints: Moving towards the robustness of monotonic noise. Neurocomputing 439: 106-121 (2021) - [j108]Manuel González, Germán González-Almagro, Isaac Triguero, José Ramón Cano, Salvador García:
Decomposition-Fusion for Label Distribution Learning. Inf. Fusion 66: 64-75 (2021) - [j107]Manuel González, Julián Luengo, José Ramón Cano, Salvador García:
Synthetic Sample Generation for Label Distribution Learning. Inf. Sci. 544: 197-213 (2021) - [j106]David López, Sergio Ramírez-Gallego, Salvador García, Ning Xiong, Francisco Herrera:
BELIEF: A distance-based redundancy-proof feature selection method for Big Data. Inf. Sci. 558: 124-139 (2021) - [j105]Pourya Shamsolmoali, Salvador García, Huiyu Zhou, M. Emre Celebi:
Advances in domain adaptation for computer vision. Image Vis. Comput. 114: 104268 (2021) - [j104]Juan-Luis Suárez, Salvador García, Francisco Herrera:
Ordinal regression with explainable distance metric learning based on ordered sequences. Mach. Learn. 110(10): 2729-2762 (2021) - [j103]Néstor Rodríguez, David López, Alberto Fernández, Salvador García, Francisco Herrera:
SOUL: Scala Oversampling and Undersampling Library for imbalance classification. SoftwareX 15: 100767 (2021) - [j102]Germán González-Almagro, Alejandro Rosales-Pérez, Julián Luengo, José Ramón Cano, Salvador García:
ME-MEOA/DCC: Multiobjective constrained clustering through decomposition-based memetic elitism. Swarm Evol. Comput. 66: 100939 (2021) - [c47]Juan-Luis Suárez, Salvador García, Francisco Herrera:
Ordinal Regression with Explainable Distance Metric Learning Based on Ordered Sequences: Extended Abstract. DSAA 2021: 1-2 - [c46]Juan-Luis Suárez, Salvador García, Francisco Herrera:
Distance Metric Learning with Prototype Selection for Imbalanced Classification. HAIS 2021: 391-402 - 2020
- [b3]Julián Luengo, Diego García-Gil, Sergio Ramírez-Gallego, Salvador García, Francisco Herrera:
Big Data Preprocessing - Enabling Smart Data. Springer 2020, ISBN 978-3-030-39104-1, pp. 1-186 - [j101]Daniel Molina, Javier Poyatos, Javier Del Ser, Salvador García, Amir Hussain, Francisco Herrera:
Comprehensive Taxonomies of Nature- and Bio-inspired Optimization: Inspiration Versus Algorithmic Behavior, Critical Analysis Recommendations. Cogn. Comput. 12(5): 897-939 (2020) - [j100]Germán González-Almagro, Julián Luengo, José Ramón Cano, Salvador García:
DILS: Constrained clustering through dual iterative local search. Comput. Oper. Res. 121: 104979 (2020) - [j99]Alejandro Barredo Arrieta, Natalia Díaz Rodríguez, Javier Del Ser, Adrien Bennetot, Siham Tabik, Alberto Barbado, Salvador García, Sergio Gil-Lopez, Daniel Molina, Richard Benjamins, Raja Chatila, Francisco Herrera:
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI. Inf. Fusion 58: 82-115 (2020) - [j98]Sergio González, Salvador García, Javier Del Ser, Lior Rokach, Francisco Herrera:
A practical tutorial on bagging and boosting based ensembles for machine learning: Algorithms, software tools, performance study, practical perspectives and opportunities. Inf. Fusion 64: 205-237 (2020) - [j97]Juan Antonio Cortés-Ibáñez, Sergio González, José Javier Valle-Alonso, Julián Luengo, Salvador García, Francisco Herrera:
Preprocessing methodology for time series: An industrial world application case study. Inf. Sci. 514: 385-401 (2020) - [j96]Juan-Luis Suárez, Salvador García, Francisco Herrera:
pyDML: A Python Library for Distance Metric Learning. J. Mach. Learn. Res. 21: 96:1-96:7 (2020) - [j95]Jacinto Carrasco, Salvador García, María del Mar Rueda, Swagatam Das, Francisco Herrera:
Recent trends in the use of statistical tests for comparing swarm and evolutionary computing algorithms: Practical guidelines and a critical review. Swarm Evol. Comput. 54: 100665 (2020) - [j94]Jesús Maillo, Salvador García, Julián Luengo, Francisco Herrera, Isaac Triguero:
Fast and Scalable Approaches to Accelerate the Fuzzy k-Nearest Neighbors Classifier for Big Data. IEEE Trans. Fuzzy Syst. 28(5): 874-886 (2020) - [c45]Hoang Lam Le, Dario Landa-Silva, Mikel Galar, Salvador García, Isaac Triguero:
A Hybrid Surrogate Model for Evolutionary Undersampling in Imbalanced Classification. CEC 2020: 1-8 - [c44]Germán González-Almagro, Alejandro Rosales-Pérez, Julián Luengo, José Ramón Cano, Salvador García:
Improving constrained clustering via decomposition-based multiobjective optimization with memetic elitism. GECCO 2020: 333-341 - [c43]Germán González-Almagro, Juan-Luis Suárez, Julián Luengo, José Ramón Cano, Salvador García:
Agglomerative Constrained Clustering Through Similarity and Distance Recalculation. HAIS 2020: 424-436 - [c42]José Ramón Cano, Julián Luengo, Salvador García:
Similarity-based and Iterative Label Noise Filters for Monotonic Classification. HICSS 2020: 1-9 - [i15]Diego García-Gil, Johan Holmberg, Salvador García, Ning Xiong, Francisco Herrera:
Smart Data based Ensemble for Imbalanced Big Data Classification. CoRR abs/2001.05759 (2020) - [i14]Daniel Molina, Javier Poyatos, Javier Del Ser, Salvador García, Amir Hussain, Francisco Herrera:
Comprehensive Taxonomies of Nature- and Bio-inspired Optimization: Inspiration versus Algorithmic Behavior, Critical Analysis and Recommendations. CoRR abs/2002.08136 (2020) - [i13]Jacinto Carrasco, Salvador García, María del Mar Rueda, Swagatam Das, Francisco Herrera:
Recent Trends in the Use of Statistical Tests for Comparing Swarm and Evolutionary Computing Algorithms: Practical Guidelines and a Critical Review. CoRR abs/2002.09227 (2020) - [i12]Sergio González, Salvador García, Sheng-Tun Li, Robert I. John, Francisco Herrera:
Fuzzy k-Nearest Neighbors with monotonicity constraints: Moving towards the robustness of monotonic noise. CoRR abs/2003.02601 (2020)
2010 – 2019
- 2019
- [j93]Diego García-Gil, Francisco Luque Sánchez, Julián Luengo, Salvador García, Francisco Herrera:
From Big to Smart Data: Iterative ensemble filter for noise filtering in Big Data classification. Int. J. Intell. Syst. 34(12): 3260-3274 (2019) - [j92]José Ramón Cano, Pedro Antonio Gutiérrez, Bartosz Krawczyk, Michal Wozniak, Salvador García:
Monotonic classification: An overview on algorithms, performance measures and data sets. Neurocomputing 341: 168-182 (2019) - [j91]José Ramón Cano, Julián Luengo, Salvador García:
Label noise filtering techniques to improve monotonic classification. Neurocomputing 353: 83-95 (2019) - [j90]Ignacio Cordón, Julián Luengo, Salvador García, Francisco Herrera, Francisco Charte:
Smartdata: Data preprocessing to achieve smart data in R. Neurocomputing 360: 1-13 (2019) - [j89]Sergio González, Salvador García, Sheng-Tun Li, Francisco Herrera:
Chain based sampling for monotonic imbalanced classification. Inf. Sci. 474: 187-204 (2019) - [j88]Diego García-Gil, Julián Luengo, Salvador García, Francisco Herrera:
Enabling Smart Data: Noise filtering in Big Data classification. Inf. Sci. 479: 135-152 (2019) - [j87]Bartosz Krawczyk, Isaac Triguero, Salvador García, Michal Wozniak, Francisco Herrera:
Instance reduction for one-class classification. Knowl. Inf. Syst. 59(3): 601-628 (2019) - [j86]David Charte, Francisco Charte, Salvador García, Francisco Herrera:
A snapshot on nonstandard supervised learning problems: taxonomy, relationships, problem transformations and algorithm adaptations. Prog. Artif. Intell. 8(1): 1-14 (2019) - [j85]M. Cristina Heredia-Gómez, Salvador García, Pedro Antonio Gutiérrez, Francisco Herrera:
OCAPIS: R package for Ordinal Classification and Preprocessing in Scala. Prog. Artif. Intell. 8(3): 287-292 (2019) - [j84]Abdellatif El Afia, Oussama Aoun, Salvador García:
Adaptive cooperation of multi-swarm particle swarm optimizer-based hidden Markov model. Prog. Artif. Intell. 8(4): 441-452 (2019) - [j83]Isaac Triguero, Diego García-Gil, Jesús Maillo, Julián Luengo, Salvador García, Francisco Herrera:
Transforming big data into smart data: An insight on the use of the k-nearest neighbors algorithm to obtain quality data. WIREs Data Mining Knowl. Discov. 9(2) (2019) - [c41]Besay Montesdeoca, Julián Luengo, Jesús Maillo, Diego García-Gil, Salvador García, Francisco Herrera:
A First Approach on Big Data Missing Values Imputation. IoTBDS 2019: 315-323 - [c40]Diego García-Gil, Alejandro Alcalde-Barros, Julián Luengo, Salvador García, Francisco Herrera:
Big Data Preprocessing as the Bridge between Big Data and Smart Data: BigDaPSpark and BigDaPFlink Libraries. IoTBDS 2019: 324-331 - [i11]Alejandro Barredo Arrieta, Natalia Díaz Rodríguez, Javier Del Ser, Adrien Bennetot, Siham Tabik, Alberto Barbado, Salvador García, Sergio Gil-Lopez, Daniel Molina, Richard Benjamins, Raja Chatila, Francisco Herrera:
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI. CoRR abs/1910.10045 (2019) - 2018
- [b2]Alberto Fernández, Salvador García, Mikel Galar, Ronaldo C. Prati, Bartosz Krawczyk, Francisco Herrera:
Learning from Imbalanced Data Sets. Springer 2018, ISBN 978-3-319-98073-7, pp. 1-377 - [j82]Alejandro Rosales-Pérez, Salvador García, Hugo Terashima-Marín, Carlos A. Coello Coello, Francisco Herrera:
MC2ESVM: Multiclass Classification Based on Cooperative Evolution of Support Vector Machines. IEEE Comput. Intell. Mag. 13(2): 18-29 (2018) - [j81]Sergio Ramírez-Gallego, Salvador García, Francisco Herrera:
Online entropy-based discretization for data streaming classification. Future Gener. Comput. Syst. 86: 59-70 (2018) - [j80]Daniel Peralta, Isaac Triguero, Salvador García, Yvan Saeys, José Manuel Benítez, Francisco Herrera:
On the use of convolutional neural networks for robust classification of multiple fingerprint captures. Int. J. Intell. Syst. 33(1): 213-230 (2018) - [j79]Zhongliang Zhang, Xinggang Luo, Sergio González, Salvador García, Francisco Herrera:
DRCW-ASEG: One-versus-One distance-based relative competence weighting with adaptive synthetic example generation for multi-class imbalanced datasets. Neurocomputing 285: 176-187 (2018) - [j78]Sergio Ramírez-Gallego, Alberto Fernández, Salvador García, Min Chen, Francisco Herrera:
Big Data: Tutorial and guidelines on information and process fusion for analytics algorithms with MapReduce. Inf. Fusion 42: 51-61 (2018) - [j77]David Charte, Francisco Charte, Salvador García, María José del Jesus, Francisco Herrera:
A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines. Inf. Fusion 44: 78-96 (2018) - [j76]Salvador García, Zhongliang Zhang, Abdulrahman H. Altalhi, Saleh Alshomrani, Francisco Herrera:
Dynamic ensemble selection for multi-class imbalanced datasets. Inf. Sci. 445-446: 22-37 (2018) - [j75]Alberto Fernández, Salvador García, Francisco Herrera, Nitesh V. Chawla:
SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Anniversary. J. Artif. Intell. Res. 61: 863-905 (2018) - [j74]Diego García-Gil, Sergio Ramírez-Gallego, Salvador García, Francisco Herrera:
Principal Components Analysis Random Discretization Ensemble for Big Data. Knowl. Based Syst. 150: 166-174 (2018) - [j73]Ignacio Cordón, Salvador García, Alberto Fernández, Francisco Herrera:
Imbalance: Oversampling algorithms for imbalanced classification in R. Knowl. Based Syst. 161: 329-341 (2018) - [j72]Sergio Ramírez-Gallego, Salvador García, José Manuel Benítez, Francisco Herrera:
A distributed evolutionary multivariate discretizer for Big Data processing on Apache Spark. Swarm Evol. Comput. 38: 240-250 (2018) - [c39]Jesús Maillo, Julián Luengo, Salvador García, Francisco Herrera, Isaac Triguero:
A preliminary study on Hybrid Spill-Tree Fuzzy k-Nearest Neighbors for big data classification. FUZZ-IEEE 2018: 1-8 - [c38]Alejandro Rosales-Pérez, Andrés Eduardo Gutiérrez-Rodríguez, Salvador García, Hugo Terashima-Marín, Carlos A. Coello Coello, Francisco Herrera:
Cooperative multi-objective evolutionary support vector machines for multiclass problems. GECCO 2018: 513-520 - [c37]Diego García-Gil, Sergio Ramírez-Gallego, Salvador García, Francisco Herrera:
On the Use of Random Discretization and Dimensionality Reduction in Ensembles for Big Data. HAIS 2018: 15-26 - [c36]José Ramón Cano, Salvador García:
A First Attempt on Monotonic Training Set Selection. HAIS 2018: 277-288 - [c35]Oussama Aoun, Abdellatif El Afia, Salvador García:
Self Inertia Weight Adaptation for the Particle Swarm Optimization. LOPAL 2018: 8:1-8:6 - [i10]David Charte, Francisco Charte, Salvador García, María José del Jesus, Francisco Herrera:
A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines. CoRR abs/1801.01586 (2018) - [i9]Sergio Ramírez-Gallego, Salvador García, Ning Xiong, Francisco Herrera:
BELIEF: A distance-based redundancy-proof feature selection method for Big Data. CoRR abs/1804.05774 (2018) - [i8]Alejandro Alcalde-Barros, Diego García-Gil, Salvador García, Francisco Herrera:
DPASF: A Flink Library for Streaming Data preprocessing. CoRR abs/1810.06021 (2018) - [i7]José Ramón Cano, Julián Luengo, Salvador García:
Label Noise Filtering Techniques to Improve Monotonic Classification. CoRR abs/1810.08914 (2018) - [i6]M. Cristina Heredia-Gómez, Salvador García, Pedro Antonio Gutiérrez, Francisco Herrera:
OCAPIS: R package for Ordinal Classification And Preprocessing In Scala. CoRR abs/1810.09733 (2018) - [i5]José Ramón Cano, Pedro Antonio Gutiérrez, Bartosz Krawczyk, Michal Wozniak, Salvador García:
Monotonic classification: an overview on algorithms, performance measures and data sets. CoRR abs/1811.07155 (2018) - [i4]David Charte, Francisco Charte, Salvador García, Francisco Herrera:
A snapshot on nonstandard supervised learning problems: taxonomy, relationships and methods. CoRR abs/1811.12044 (2018) - [i3]Juan-Luis Suárez, Salvador García, Francisco Herrera:
A Tutorial on Distance Metric Learning: Mathematical Foundations, Algorithms and Software. CoRR abs/1812.05944 (2018) - 2017
- [j71]Zhongliang Zhang, Xinggang Luo, Salvador García, Francisco Herrera:
Cost-Sensitive back-propagation neural networks with binarization techniques in addressing multi-class problems and non-competent classifiers. Appl. Soft Comput. 56: 357-367 (2017) - [j70]José Ramón Cano, Salvador García:
Training set selection for monotonic ordinal classification. Data Knowl. Eng. 112: 94-105 (2017) - [j69]José Ramón Cano, Naif R. Aljohani, Rabeeh Ayaz Abbasi, Jalal S. Alowibdi, Salvador García:
Prototype selection to improve monotonic nearest neighbor. Eng. Appl. Artif. Intell. 60: 128-135 (2017) - [j68]Isaac Triguero, Sergio González, Jose M. Moyano, Salvador García, Jesús Alcalá-Fdez, Julián Luengo, Alberto Fernández, María José del Jesus, Luciano Sánchez, Francisco Herrera:
KEEL 3.0: An Open Source Software for Multi-Stage Analysis in Data Mining. Int. J. Comput. Intell. Syst. 10(1): 1238-1249 (2017) - [j67]Sergio Ramírez-Gallego, Bartosz Krawczyk, Salvador García, Michal Wozniak, Francisco Herrera:
A survey on data preprocessing for data stream mining: Current status and future directions. Neurocomputing 239: 39-57 (2017) - [j66]Muhammad Aslam Jarwar, Rabeeh Ayaz Abbasi, Mubashar Mushtaq, Onaiza Maqbool, Naif R. Aljohani, Ali Daud, Jalal S. Alowibdi, José Ramón Cano, Salvador García, Ilyoung Chong:
CommuniMents: A Framework for Detecting Community Based Sentiments for Events. Int. J. Semantic Web Inf. Syst. 13(2): 87-108 (2017) - [j65]Daniel Peralta, Salvador García, José Manuel Benítez, Francisco Herrera:
Minutiae-based fingerprint matching decomposition: Methodology for big data frameworks. Inf. Sci. 408: 198-212 (2017) - [j64]Zhongliang Zhang, Xinggang Luo, Salvador García, Jiafu Tang, Francisco Herrera:
Exploring the effectiveness of dynamic ensemble selection in the one-versus-one scheme. Knowl. Based Syst. 125: 53-63 (2017) - [j63]Daniel Peralta, Isaac Triguero, Salvador García, Yvan Saeys, José Manuel Benítez, Francisco Herrera:
Distributed incremental fingerprint identification with reduced database penetration rate using a hierarchical classification based on feature fusion and selection. Knowl. Based Syst. 126: 91-103 (2017) - [j62]Javier García, Habib M. Fardoun, Daniyal M. Alghazzawi, José Ramón Cano, Salvador García:
MoNGEL: monotonic nested generalized exemplar learning. Pattern Anal. Appl. 20(2): 441-452 (2017) - [j61]Sergio González, Salvador García, Marcelino Lázaro, Aníbal R. Figueiras-Vidal, Francisco Herrera:
Class Switching according to Nearest Enemy Distance for learning from highly imbalanced data-sets. Pattern Recognit. 70: 12-24 (2017) - [j60]Alejandro Rosales-Pérez, Salvador García, Jesus A. Gonzalez, Carlos A. Coello Coello, Francisco Herrera:
An Evolutionary Multiobjective Model and Instance Selection for Support Vector Machines With Pareto-Based Ensembles. IEEE Trans. Evol. Comput. 21(6): 863-877 (2017) - [j59]Jesús Alcalá-Fdez, Rafael Alcalá, Sergio González, Yusuke Nojima, Salvador García:
Evolutionary Fuzzy Rule-Based Methods for Monotonic Classification. IEEE Trans. Fuzzy Syst. 25(6): 1376-1390 (2017) - [j58]Sergio Ramírez-Gallego, Bartosz Krawczyk, Salvador García, Michal Wozniak, José Manuel Benítez, Francisco Herrera:
Nearest Neighbor Classification for High-Speed Big Data Streams Using Spark. IEEE Trans. Syst. Man Cybern. Syst. 47(10): 2727-2739 (2017) - [c34]Jesús Maillo, Julián Luengo, Salvador García, Francisco Herrera, Isaac Triguero:
Exact fuzzy k-nearest neighbor classification for big datasets. FUZZ-IEEE 2017: 1-6 - [c33]Jacinto Carrasco, Salvador García, María del Mar Rueda, Francisco Herrera:
rNPBST: An R Package Covering Non-parametric and Bayesian Statistical Tests. HAIS 2017: 281-292 - [i2]Daniel Peralta, Isaac Triguero, Salvador García, Yvan Saeys, José Manuel Benítez, Francisco Herrera:
Fingerprint classification with a new deep neural network model: robustness for different captures of the same fingerprints. CoRR abs/1703.07270 (2017) - [i1]Diego García-Gil, Julián Luengo, Salvador García, Francisco Herrera:
Enabling Smart Data: Noise filtering in Big Data classification. CoRR abs/1704.01770 (2017) - 2016
- [j57]Nele Verbiest, Joaquín Derrac, Chris Cornelis, Salvador García, Francisco Herrera:
Evolutionary wrapper approaches for training set selection as preprocessing mechanism for support vector machines: Experimental evaluation and support vector analysis. Appl. Soft Comput. 38: 10-22 (2016) - [j56]Javier García, Adnan Al-bar, Naif R. Aljohani, José Ramón Cano, Salvador García:
Hyperrectangles Selection for Monotonic Classification by Using Evolutionary Algorithms. Int. J. Comput. Intell. Syst. 9(1): 184-201 (2016) - [j55]Daniel Peralta, Isaac Triguero, Salvador García, Francisco Herrera, José Manuel Benítez:
DPD-DFF: A dual phase distributed scheme with double fingerprint fusion for fast and accurate identification in large databases. Inf. Fusion 32: 40-51 (2016) - [j54]Joaquín Derrac, Francisco Chiclana, Salvador García, Francisco Herrera:
Evolutionary fuzzy k-nearest neighbors algorithm using interval-valued fuzzy sets. Inf. Sci. 329: 144-163 (2016) - [j53]Salvador García, Julián Luengo, Francisco Herrera:
Tutorial on practical tips of the most influential data preprocessing algorithms in data mining. Knowl. Based Syst. 98: 1-29 (2016) - [j52]Zhongliang Zhang, Bartosz Krawczyk, Salvador García, Alejandro Rosales-Pérez, Francisco Herrera:
Empowering one-vs-one decomposition with ensemble learning for multi-class imbalanced data. Knowl. Based Syst. 106: 251-263 (2016) - [j51]Salvador Gutiérrez, Salvador García:
Landmark-based music recognition system optimisation using genetic algorithms. Multim. Tools Appl. 75(24): 16905-16922 (2016) - [j50]Pedro Antonio Gutiérrez, Salvador García:
Current prospects on ordinal and monotonic classification. Prog. Artif. Intell. 5(3): 171-179 (2016) - [j49]