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Yailé Caballero Mota
- > Home > Persons > Yailé Caballero Mota
Publications
- 2022
- [j14]Yanela Rodríguez Alvarez, María Matilde García Lorenzo, Yailé Caballero Mota, Yaima Filiberto Cabrera, Isabel M. García Hilarión, Daniela Machado Montes de Oca, Rafael Bello Pérez:
Fuzzy prototype selection-based classifiers for imbalanced data. Case study. Pattern Recognit. Lett. 163: 183-190 (2022) - [p2]Rafael Bello, María M. García, Yaile Caballero, Alejandro Rosete, Yanela Rodríguez:
Applications of Computational Intelligence in the Studies of Covid-19. Computational Intelligence Methodologies Applied to Sustainable Development Goals 2022: 63-80 - 2018
- [c20]Yanela Rodríguez Alvarez, Rafael Bello Pérez, Yailé Caballero Mota, Yaima Filiberto Cabrera, Yumilka B. Fernandez Hernandez, Mabel Frias Dominguez:
Fuzzy Design of Nearest Prototype Classifier. MICAI (1) 2018: 391-400 - 2017
- [c19]Yanela Rodríguez Alvarez, Yailé Caballero Mota, Rafael Bello Pérez, Yaima Filiberto Cabrera, Yumilka B. Fernandez Hernandez, Mabel Frias Dominguez:
An Approach to Solve Classification Problems on Domains with Hubness Using Rough Sets and Nearest Prototype. MICAI (Special Session) 2017: 34-38 - 2016
- [j12]Enislay Ramentol, I. Gondres, S. Lajes, Rafael Bello, Yaile Caballero, Chris Cornelis, Francisco Herrera:
Fuzzy-rough imbalanced learning for the diagnosis of High Voltage Circuit Breaker maintenance: The SMOTE-FRST-2T algorithm. Eng. Appl. Artif. Intell. 48: 134-139 (2016) - 2015
- [j11]Yumilka B. Fernandez Hernandez, Rafael Bello, Yaima Filiberto, Mabel Frias Dominguez, Lenniet Coello Blanco, Yailé Caballero Mota:
An Approach for Prototype Generation based on Similarity Relations for Problems of Classification. Computación y Sistemas 19(1) (2015) - [j9]Enislay Ramentol, Sarah Vluymans, Nele Verbiest, Yaile Caballero, Rafael Bello, Chris Cornelis, Francisco Herrera:
IFROWANN: Imbalanced Fuzzy-Rough Ordered Weighted Average Nearest Neighbor Classification. IEEE Trans. Fuzzy Syst. 23(5): 1622-1637 (2015) - 2012
- [j3]Enislay Ramentol, Yaile Caballero, Rafael Bello, Francisco Herrera:
SMOTE-RSB *: a hybrid preprocessing approach based on oversampling and undersampling for high imbalanced data-sets using SMOTE and rough sets theory. Knowl. Inf. Syst. 33(2): 245-265 (2012) - 2011
- [c12]Yaima Filiberto Cabrera, Rafael Bello Pérez, Yailé Caballero Mota, Gonzalo Ramos-Jiménez:
Improving the MLP Learning by Using a Method to Calculate the Initial Weights of the Network Based on the Quality of Similarity Measure. MICAI (2) 2011: 351-362 - 2010
- [c11]Yaima Filiberto, Yaile Caballero, Rafael Larrua, Rafael Bello:
A method to build similarity relations into extended Rough Set Theory. ISDA 2010: 1314-1319 - [c10]Yaima Filiberto, Rafael Bello, Yaile Caballero, Rafael Larrua:
Using PSO and RST to Predict the Resistant Capacity of Connections in Composite Structures. NICSO 2010: 359-370 - [p1]Yaile Caballero, Rafael Bello, Leticia Arco, María M. García, Enislay Ramentol:
Knowledge Discovery Using Rough Set Theory. Advances in Machine Learning I 2010: 367-383 - 2007
- [j1]Beitmantt Cárdenas, Yaile Caballero, Rafael Bello:
La Teoría de los Conjuntos Aproximados y las técnicas de Boostrap para la Edición de Conjuntos de Entrenamiento. Su aplicación en el pronóstico metereológico. Rev. Avances en Sistemas Informática 4(3): 165-170 (2007) - [c9]Yaile Caballero, Rafael Bello, Leticia Arco, María M. García:
Rough Set Theory Measures to Knowledge Generation. ISDA 2007: 401-406 - [c8]Yaile Caballero, Delia Alvarez, Rafael Bello, María M. García:
Feature Selection Algorithms Using Rough Set Theory. ISDA 2007: 407-411 - [c7]Yaile Caballero, Leticia Arco, Rafael Bello, Jorge Marx Gómez:
New Measures for Evaluating Decision Systems Using Rough Set Theory: The Application in Seasonal Weather Forecasting. ITEE 2007: 161-173 - 2006
- [c6]Yaile Caballero, Rafael Bello, Delia Alvarez, María M. García, Yaimara Pizano:
Improving the k-NN method: Rough Set in edit training set. IFIP PPAI 2006: 21-30 - [c5]Yaile Caballero, Rafael Bello, Delia Alvarez, María M. García:
Two new feature selection algorithms with Rough Sets Theory. IFIP AI 2006: 209-216 - [c4]Yaile Caballero, Rafael Bello, Alberto Taboada-Crispí, Ann Nowé, María M. García, Gladys Casas:
A New Measure Based in the Rough Set Theory to Estimate the Training Set Quality. SYNASC 2006: 133-140 - 2005
- [c3]Rafael Bello, Ann Nowé, Yaile Caballero, Yudel Gómez, Peter Vrancx:
A model based on ant colony system and rough set theory to feature selection. GECCO 2005: 275-276 - [c2]Yaile Caballero, Simone Joseph, Yuniesky Lezcano, Rafael Bello, María M. García, Yaimara Pizano:
Using rough sets to edit training set in k-NN method. ISDA 2005: 456-463
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