Publications Listing

Papers published in Journals (C. Cornelis)

Number of Results: 26

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[2324] S. Vluymans, A. Fernandez, C. Cornelis, Y. Saeys, F. Herrera. Dynamic Affinity-based Classification of Multi-Class Imbalanced Data with One-vs-One Decomposition: a Fuzzy Rough Set Approach. Knowledge and Information Systems 56:1 (2018) 55–84. doi: 10.1007/s10115-017-1126-1
[2644] S. Vluymans, C. Cornelis, F. Herrera, Y. Saeys. Multi-Label Classification using a Fuzzy Rough Neighborhood Consensus. Information Sciences, vol. 433-434 (2018), 96-114.. doi: 10.1016/j.ins.2017.12.034

[1968] N. Verbiest, J. Derrac, C. Cornelis, S. García, F. Herrera. Evolutionary Wrapper Approaches for Training Set Selection as Preprocessing Mechanism for Support Vector Machines: Experimental Evaluation and Support Vector Analysis. Applied Soft Computing 38 (2016) 10-22. doi: 10.1016/j.asoc.2015.09.006
[2101] S. Vluymans, I. Triguero, C. Cornelis, Y. Saeys. EPRENNID: An Evolutionary Prototype Reduction Based Ensemble for Nearest Neighbor Classification of Imbalanced Data. Neurocomputing 216 (2016) 596-610. doi: 10.1016/j.neucom.2016.08.026
[2009] E. Ramentol, I. Gondres, S. Lajes, R. Bello, Y. Caballero, C. Cornelis, F. Herrera. Fuzzy-rough imbalanced learning for the diagnosis of High Voltage Circuit Breaker maintenance: The SMOTE-FRST-2T algorithm. Engineering Applications of Artificial Intelligence 48 (2016) 134-139. doi: 10.1016/j.engappai.2015.10.009
[2013] S. Vluymans, D. Sanchez-Tarrago, Y. Saeys, C. Cornelis, F. Herrera. Fuzzy Multi-Instance Classifiers. IEEE Transactions on Fuzzy Systems 24:6 (2016) 1395-1409. doi: 10.1109/TFUZZ.2016.2516582
[2016] S. Vluymans, D. Sánchez-Tarragó, Y. Saeys, C. Cornelis, F. Herrera. Fuzzy rough classifiers for class imbalanced multi-instance data. Pattern Recognition 53 (2016) 36-45. doi: 10.1016/j.patcog.2015.12.002

[1846] E. Ramentol, S. Vluymans, N. Verbiest, Y. Caballero, R. Bello, C. Cornelis, F. Herrera. IFROWANN: Imbalanced Fuzzy-Rough Ordered Weighted Average Nearest Neighbor Classification. IEEE Transactions on Fuzzy Systems 23:5 (2015) 1622-1637. doi: 10.1109/TFUZZ.2014.2371472
[1923] L. D’eer, N. Verbiest, C. Cornelis, L. Godo. A Comprehensive Study of Implicator-Conjunctor Based and Noise-Tolerant Fuzzy Rough Sets: Definitions, Properties and Robustness Analysis. Fuzzy Sets and Systems 275 (2015) 1-38. doi: 10.1016/j.fss.2014.11.018

[1667] M. Restrepo, C. Cornelis, J. Gómez. Duality, Conjugacy and Adjointness of Approximation Operators in Covering Based Rough Sets. International Journal of Approximate Reasoning 55:1 (2014) 469-485. doi: 10.1016/j.ijar.2013.08.002
[1671] C. Cornelis, J. Medina, N. Verbiest. Multi-adjoint fuzzy rough sets: Definition, properties and attribute selection. International Journal of Approximate Reasoning 55:1 (2014) 412-426. doi: 10.1016/j.ijar.2013.09.007
[1736] D.S. Tarragó, C. Cornelis, R. Bello, F. Herrera. A Multi-Instance Learning Wrapper based on the Rocchio Classifier for Web Index Recommendation. Knowledge-Based Systems 59 (2014) 173-181. doi: 10.1016/j.knosys.2014.01.008
[1773] N. Verbiest, E. Ramentol, C. Cornelis, F. Herrera. Preprocessing Noisy Imbalanced Datasets using SMOTE enhanced with Fuzzy Rough Prototype Selection. Applied Soft Computing 22 (2014) 511-517. doi: 10.1016/j.asoc.2014.05.023
[1817] L. S. Riza, Andrzej Janusz, C. Bergmeir, C. Cornelis, F. Herrera, Dominik Slezak, J.M. Benítez. Implementing algorithms of rough set theory and fuzzy rough set theory in the R package "RoughSets". Information Sciences 287 (2014) 68-89.
[1922] M. Restrepo, C. Cornelis, J. Gómez. Partial Order Relation for Approximation Operators in Covering Based Rough Sets. Information Sciences 284 (2014) 44-59. doi: 10.1016/j.ins.2014.06.032

[1537] J. Derrac, N. Verbiest, S. García, C. Cornelis, F. Herrera. On the use of Evolutionary Feature Selection for Improving Fuzzy Rough Set Based Prototype Selection. Soft Computing 17:2 (2013) 223-238. doi: 10.1007/s00500-012-0888-3
[1562] G. Hurtado, S. Schockaert, C. Cornelis, H. Naessens. Using Semi-Structured Data for Assessing Research Paper Similarity. Information Sciences 221:1 (2013) 245-261. doi: /10.1016/j.ins.2012.09.044
[1634] N. Verbiest, C. Cornelis, F. Herrera. FRPS: A Fuzzy Rough Prototype Selection method. Pattern Recognition 46:10 (2013) 2770-2782. doi: 10.1016/j.patcog.2013.03.004
[1654] P. Victor, N. Verbiest, C. Cornelis, M. De Cock. Enhancing the Trust-Based Recommendation Process with Explicit Distrust. ACM Transactions on the Web 7(2) (2013). doi: 10.1145/2460383.2460385

[1428] J. Derrac, C. Cornelis, S. García, F. Herrera. Enhancing Evolutionary Instance Selection Algorithms by means of Fuzzy Rough Set based Feature Selection. Information Sciences 186:1 (2012) 73-92. doi: 10.1016/j.ins.2011.09.027
[1534] N. Verbiest, C. Cornelis, P. Victor, E. Herrera-Viedma. Trust and distrust aggregation enhanced with path length incorporation. Fuzzy Sets and Systems , 202:1 (2012) 61–74. doi: 10.1016/j.fss.2012.02.007
[1616] B. Van Gasse, G. Deschrijver, C. Cornelis, E. E. Kerre. The Standard Completeness of Interval-Valued Monoidal t-Norm Based Logic. Information Sciences 189:1 (2012) 63-76. doi: 10.1016/j.ins.2011.11.043

[1325] P. Victor, C. Cornelis, M. De Cock, E. Herrera-Viedma. Practical Aggregation Operators for Gradual Trust and Distrust. Fuzzy Sets and Systems 184:1 (2011) 126-147. doi: 10.1016/j.fss.2010.10.015
[1454] Richard Jensen, C. Cornelis. Fuzzy Rough Nearest Neighbour Classification and Prediction. Theoretical Computer Science 412:42 (2011) 5871-5884. doi: 10.1016/j.tcs.2011.05.040
[1455] T. Fayruzov, J. Janssen, D. Vermeir, C. Cornelis, M. De Cock. Modelling Gene and Protein Regulatory Networks with Answer Set Programming. International Journal of Data Mining and Bioinformatics 5:2 (2011) 209-229. doi: 10.1504/IJDMB.2011.039178
[1456] P. Victor, C. Cornelis, M. De Cock, A. Teredesai. Trust- and Distrust-Based Recommendations for Controversial Reviews. IEEE Intelligent Systems 26:1 (2011) 48-55. doi: 10.1109/MIS.2011.22