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Roberto Alejo
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2020 – today
- 2024
- [j13]Itzel M. Abundez B.
, Roberto Alejo
Threshold Active Learning Approach for Physical Violence Detection on Images Obtained from Video (Frame-Level) Using Pre-Trained Deep Learning Neural Network Models. Algorithms 17(7): 316 (2024) - 2023
- [c28]Itzel Abundez Barrera
Empirical Analysis on the Effectiveness of Pre-trained Models in the Identification of Physical Violence Against Women in Videos for a Multi-class Approach. DMBD (1) 2023: 152-164 - 2022
- [c27]Grisel Miranda-Piña
Clustering Analysis in the Student Academic Activities on COVID-19 Pandemic in Mexico. ICIC (3) 2022: 67-79 - [c26]Carlos Castorena
Artificial Neural Networks for COVID-19 Forecasting in Mexico: An Empirical Study. ICIC (1) 2022: 168-179 - [c25]A. Bolívar
A Preliminary Study of SMOTE on Imbalanced Big Datasets When Dealing with Sparse and Dense High Dimensionality. MCPR 2022: 46-55 - 2021
- [c24]Grisel Miranda, Roberto Alejo, Carlos Castorena, Eréndira Rendón, Javier Illescas, Vicente García
Deep Neural Network to Detect Gender Violence on Mexican Tweets. IWAIPR 2021: 24-32 - 2020
- [j12]C. Guadalupe Origel-Rivas, Eréndira Rendón Lara, Itzel Abundez Barrera, Roberto Alejo Eleuterio:
Redes neuronales artificiales y árboles de decisión para la clasificación con datos categóricos. Res. Comput. Sci. 149(8): 541-554 (2020) - [c23]Angélica Guzmán Ponce
A Metaheuristic Algorithm to Face the Graph Coloring Problem. HAIS 2020: 195-208 - [c22]Graciela García-Rueda, Rosa Maria Valdovinos
Analysis of Repair Costs of Scholar Buildings Affected by Earthquakes Using Data Mining. Case Study: Earthquakes of 2017 in Mexico. MCPR 2020: 45-56
2010 – 2019
- 2019
- [c21]V. M. González-Barcenas, Eréndira Rendón
Addressing the Big Data Multi-class Imbalance Problem with Oversampling and Deep Learning Neural Networks. IbPRIA (1) 2019: 216-224 - 2018
- [j11]J. Horacio Pacheco-Sánchez, R. D. Vera-Torres, Roberto Alejo Eleuterio
Bayesian Learning on Discrete Systems of Two Classes. Int. J. Pattern Recognit. Artif. Intell. 32(1): 1860013:1-1860013:28 (2018) - [j10]H. Cruz-Reyes, Adriana Reyes-Nava, Eréndira Rendón Lara, Roberto Alejo:
Estudio del desbalance de clases en bases de datos de microarrays de expresión genética mediante técnicas de Deep Learning. Res. Comput. Sci. 147(5): 197-207 (2018) - [j9]Angélica Guzmán Ponce, Rosa María Valdovinos Rosas, José Raymundo Marcial-Romero, Roberto Alejo Eleuterio:
Entornos de trabajo para procesamiento de datos masivos y aprendizaje automático. Res. Comput. Sci. 147(5): 225-237 (2018) - [c20]Adriana Reyes-Nava
Using Deep Learning to Classify Class Imbalanced Gene-Expression Microarrays Datasets. CIARP 2018: 46-54 - [c19]Adriana Reyes-Nava
Performance Analysis of Deep Neural Networks for Classification of Gene-Expression Microarrays. MCPR 2018: 105-115 - 2017
- [j8]Roberto Alejo
An improved dynamic sampling back-propagation algorithm based on mean square error to face the multi-class imbalance problem. Neural Comput. Appl. 28(10): 2843-2857 (2017) - [j7]Adriana Reyes-Nava, Allan Flores-Fuentes, Roberto Alejo, Eréndira Rendón Lara:
Minería de datos aplicada para la identificación de factores de riesgo en alumnos. Res. Comput. Sci. 139: 177-189 (2017) - [i1]M. A. López, José Raymundo Marcial-Romero, Guillermo De Ita Luna, Héctor A. Montes Venegas, Roberto Alejo:
A Linear Time Algorithm for Solving #2SAT on Cactus Formulas. CoRR abs/1702.08581 (2017) - 2015
- [j6]Roberto Alejo
An Efficient Over-sampling Approach Based on Mean Square Error Back-propagation for Dealing with the Multi-class Imbalance Problem. Neural Process. Lett. 42(3): 603-617 (2015) - [j5]José Luis Aguirre Mendiola, Rosa María Valdovinos Rosas, Juan Alberto Antonio Velázquez, Roberto Alejo Eleuterio, José Raymundo Marcial-Romero:
Análisis de deserción escolar con minería de datos. Res. Comput. Sci. 93: 71-82 (2015) - [c18]Roberto Alejo
Analysing the Safe, Average and Border Samples on Two-Class Imbalance Problems in the Back-Propagation Domain. CIARP 2015: 699-707 - 2014
- [c17]Juan Pablo Sánchez-Crisostomo, Roberto Alejo
Empirical Analysis of Assessments Metrics for Multi-class Imbalance Learning on the Back-Propagation Context. ICSI (2) 2014: 17-23 - 2013
- [j4]Rosa Maria Valdovinos, Rosalinda Abad Sánchez, Roberto Alejo, Edgar Herrera, Adrián Trueba:
Tratamiento del desbalance en problemas con múltiples clases con ECOC. Computación y Sistemas 17(4) (2013) - [j3]Roberto Alejo
A hybrid method to face class overlap and class imbalance on neural networks and multi-class scenarios. Pattern Recognit. Lett. 34(4): 380-388 (2013) - [c16]Roberto Alejo
Assessments Metrics for Multi-class Imbalance Learning: A Preliminary Study. MCPR 2013: 335-343 - [c15]Mónica Santibáñez, Rosa Maria Valdovinos
Applicability of Cluster Validation Indexes for Large Data Sets. MICAI (Special Sessions) 2013: 187-193 - 2012
- [c14]P. Toribio, Roberto Alejo, Rosa Maria Valdovinos
Using Gabriel graphs in Borderline-SMOTE to deal with severe two-class imbalance problems on neural networks. CCIA 2012: 29-36 - [c13]Roberto Alejo
A Modified Back-Propagation Algorithm to Deal with Severe Two-Class Imbalance Problems on Neural Networks. MCPR 2012: 265-272 - 2011
- [c12]Roberto Alejo
Resampling Methods versus Cost Functions for Training an MLP in the Class Imbalance Context. ISNN (2) 2011: 19-26 - [c11]Roberto Alejo
Back Propagation with Balanced MSE Cost Function and Nearest Neighbor Editing for Handling Class Overlap and Class Imbalance. IWANN (1) 2011: 199-206 - 2010
- [b1]Roberto Alejo:
Análisis del error en redes neuronales: Corrección de los datos y distribuciones no balanceadas. Jaume I University, Spain, 2010 - [c10]Roberto Alejo
Edited Nearest Neighbor Rule for Improving Neural Networks Classifications. ISNN (1) 2010: 303-310 - [c9]Roberto Alejo
Cost-Sensitive Neural Networks and Editing Techniques for Imbalance Problems. MCPR 2010: 180-188
2000 – 2009
- 2009
- [c8]Roberto Alejo
The Multi-Class Imbalance Problem: Cost Functions with Modular and Non-Modular Neural Networks. ISNN (4) 2009: 421-431 - [c7]Laura Cleofas, Rosa Maria Valdovinos
Use of Ensemble Based on GA for Imbalance Problem. ISNN (2) 2009: 547-554 - 2008
- [c6]Roberto Alejo
An Empirical Study for the Multi-class Imbalance Problem with Neural Networks. CIARP 2008: 479-486 - 2007
- [c5]Vicente García
When Overlapping Unexpectedly Alters the Class Imbalance Effects. IbPRIA (2) 2007: 499-506 - [c4]Roberto Alejo
Improving the Performance of the RBF Neural Networks Trained with Imbalanced Samples. IWANN 2007: 162-169 - 2006
- [c3]Vicente García
Combined Effects of Class Imbalance and Class Overlap on Instance-Based Classification. IDEAL 2006: 371-378 - [c2]Roberto Alejo
Improving the Classification Accuracy of RBF and MLP Neural Networks Trained with Imbalanced Samples. IDEAL 2006: 464-471 - 2003
- [j2]José Salvador Sánchez
Analysis of new techniques to obtain quality training sets. Pattern Recognit. Lett. 24(7): 1015-1022 (2003) - 2001
- [j1]Ricardo Barandela, Eduardo Gasca, Roberto Alejo:
Correccion de la Muestra para el Aprendizaje del Perceptron Multicapa. Inteligencia Artif. 5(13): 2-9 (2001) - [c1]José Salvador Sánchez, Ricardo Barandela, A. I. Marqués, Roberto Alejo
Performance Evaluation of Prototype Selection Algorithms for Nearest Neighbor Classification. SIBGRAPI 2001: 44-50
Coauthor Index
aka: Eréndira Rendón
aka: J. H. Pacheco-Sanchez
aka: Rosa María Valdovinos Rosas
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last updated on 2024-10-07 22:14 CEST by the dblp team
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