R. Alejo

发表

The class imbalance problem in pattern classiﬁcation and learning

R. A. Mollineda, J. Sotoca, V. García, 2009 .

Thermal Neutron Classification in the Hohlraum Using Artificial Neural Networks

R. M. Valdovinos, R. Alejo, H. A. Montes-Venegas, 2015 .

A Metaheuristic Algorithm to Face the Graph Coloring Problem

Roberto Alejo, Rosa Maria Valdovinos, José Raymundo Marcial-Romero, 2020, HAIS.

When Overlapping Unexpectedly Alters the Class Imbalance Effects

José Martínez Sotoca, Roberto Alejo, José Salvador Sánchez, 2007, IbPRIA.

Comparative study of methods to obtain the number of hidden neurons of an auto-encoder in a high-dimensionality context

R. Alejo, E. E. Granda-Gutiérrez, Hector R. Vega-Gutierrez, 2020, IEEE Latin America Transactions.

Addressing the Big Data Multi-class Imbalance Problem with Oversampling and Deep Learning Neural Networks

Eréndira Rendón Lara, Roberto Alejo, Rosa Maria Valdovinos, 2019, IbPRIA.

Analysis of new techniques to obtain quality training sets

Roberto Alejo, José Salvador Sánchez, Ricardo Barandela, 2003, Pattern Recognit. Lett..

Data Sampling Methods to Deal With the Big Data Multi-Class Imbalance Problem

Eréndira Rendón, R. Alejo, Carlos Castorena, 2020, Applied Sciences.

A Selective Dynamic Sampling Back-Propagation Approach for Handling the Two-Class Imbalance Problem

Juan Monroy-de-Jesús, Erika López-González, R. Alejo, 2016 .

Deep Neural Network for Gender-Based Violence Detection on Twitter Messages

R. Alejo, Itzel Abundez, Eréndira Rendón, 2021, Mathematics.

Combined Effects of Class Imbalance and Class Overlap on Instance-Based Classification

José Martínez Sotoca, Roberto Alejo, José Salvador Sánchez, 2006, IDEAL.

Making Accurate Credit Risk Predictions with Cost-Sensitive MLP Neural Networks

José Salvador Sánchez, Vicente García, A. I. Marqués, 2013 .

Improving the Performance of the RBF Neural Networks Trained with Imbalanced Samples

José Martínez Sotoca, Roberto Alejo, José Salvador Sánchez, 2007, IWANN.

Use of Ensemble Based on GA for Imbalance Problem

Roberto Alejo, Rosa Maria Valdovinos, Vicente García, 2009, ISNN.

An Efficient Over-sampling Approach Based on Mean Square Error Back-propagation for Dealing with the Multi-class Imbalance Problem

V. García, R. Alejo, J. Pacheco-Sánchez, 2015, Neural Processing Letters.

An improved dynamic sampling back-propagation algorithm based on mean square error to face the multi-class imbalance problem

Roberto Alejo, Juan Monroy-de-Jesús, J. Horacio Pacheco-Sánchez, 2017, Neural Computing and Applications.

Analysing the Safe, Average and Border Samples on Two-Class Imbalance Problems in the Back-Propagation Domain

Roberto Alejo, Juan Monroy-de-Jesús, J. Horacio Pacheco-Sánchez, 2015, CIARP.

A hybrid method to face class overlap and class imbalance on neural networks and multi-class scenarios

Roberto Alejo, J. Horacio Pacheco-Sánchez, Rosa Maria Valdovinos, 2013, Pattern Recognit. Lett..

Clustering Algorithms: An Application for Adsorption Kinetic Curves

Eréndira Rendón, R. Alejo, Jose Luis Garcia Rivas, 2021, IEEE Latin America Transactions.

Applicability of Cluster Validation Indexes for Large Data Sets

Eréndira Rendón Lara, Roberto Alejo, Rosa Maria Valdovinos, 2013, 2013 12th Mexican International Conference on Artificial Intelligence.

Correcting the Training Data

Eduardo Gasca, Ricardo Barandela, R. Alejo, 2003 .

Analysis of Repair Costs of Scholar Buildings Affected by Earthquakes Using Data Mining. Case Study: Earthquakes of 2017 in Mexico

Roberto Alejo, Jesús Valdés-González, J. Leonardo González-Ruiz, 2020, MCPR.

Advances in Swarm Intelligence

Roberto Alejo, J. Horacio Pacheco-Sánchez, Juan Pablo Sánchez-Crisostomo, 2014, Lecture Notes in Computer Science.

Empirical Analysis of Assessments Metrics for Multi-class Imbalance Learning on the Back-Propagation Context

Roberto Alejo, J. Horacio Pacheco-Sánchez, Rosa Maria Valdovinos, 2014, ICSI.

Edited Nearest Neighbor Rule for Improving Neural Networks Classifications

José Martínez Sotoca, Roberto Alejo, Rosa Maria Valdovinos, 2010, ISNN.

Cost-Sensitive Neural Networks and Editing Techniques for Imbalance Problems

José Martínez Sotoca, Roberto Alejo, Rosa Maria Valdovinos, 2010, MCPR.

Using Gabriel graphs in Borderline-SMOTE to deal with severe two-class imbalance problems on neural networks

Roberto Alejo, J. Horacio Pacheco-Sánchez, Rosa Maria Valdovinos, 2012, CCIA.