Listar DIAN-Artículos, capítulos... por autor "ba2ec08f-f0ad-4cd8-81ae-66bb84ced940"

Mostrando ítems 1-12 de 12

    • A general framework for boosting feature subset selection algorithms 

      Pérez Rodríguez, Javier; Haro García, Aída de; Romero-del-Castillo, Juan A.; García Pedrajas, Nicolás (Elsevier, 2018)
      Feature selection is one of the most important tasks in many machine learning and data mining problems. Due to the increasing size of the problems, removing useless, erroneous or noisy features is frequently an initial ...

    • Cooperative coevolutionary instance selection for multilabel problems 

      García Pedrajas, Nicolás; Cerruela García, Gonzalo (Elsevier, 2021)
      Multilabel classification as a data mining task has recently attracted greater research interest. Many current data mining applications address problems having instances that belong to more than one class, which requires ...

    • Effective Feature Selection Method for Class-Imbalance Datasets Applied to Chemical Toxicity Prediction 

      Antelo-Collado, Aurelio; Carrasco-Velar, Ramón; García Pedrajas, Nicolás; Cerruela García, Gonzalo (American Chemical Society, 2021)
      During the drug development process, it is common to carry out toxicity tests and adverse effect studies, which are essential to guarantee patient safety and the success of the research. The use of in silico quantitative ...

    • Effects of Molecular Representation in Predicting the Biological Activity using SVM and PLS Approaches 

      Cerruela García, Gonzalo; Luque Ruiz, Irene; García Pedrajas, Nicolás; Gómez-Nieto, Miguel Ángel (2014)
      In this work we study and analyze the behavior of different representational spaces for molecular activity prediction. Representational spaces based on fingerprint similarity, structural similarity using maximum ...

    • Graph-Based Feature Selection Approach for Molecular Activity Prediction 

      Cerruela García, Gonzalo; Cuevas-Muñoz, José Manuel; García Pedrajas, Nicolás (ACS, 2022)
      In the construction of QSAR models for the prediction of molecular activity, feature selection is a common task aimed at improving the results and understanding of the problem. The selection of features allows elimination ...

    • Graph-Based Feature Selection Approach for Molecular Activity Prediction 

      Cerruela García, Gonzalo; Cuevas-Muñoz, José Manuel; García Pedrajas, Nicolás (American Chemical Society, 2022)
      In the construction of QSAR models for the prediction of molecular activity, feature selection is a common task aimed at improving the results and understanding of the problem. The selection of features allows elimination ...

    • Instance selection for multi-label learning based on a scalable evolutionary algorithm 

      Romero-del-Castillo, Juan A.; Ortiz-Boyer, Domingo; García Pedrajas, Nicolás (IEEE, 2021)
      Multi-label classification has recently attracted greater research interest as a data mining task. Many current ap- plications in data mining address problems having instances that belong to more than one class, which ...

    • Local-based k values for multi-label k-nearest neighbors rule 

      Romero-del-Castillo, Juan A.; Mendoza-Hurtado, Manuel; Ortiz-Boyer, Domingo; García Pedrajas, Nicolás (Elsevier, 2022)
      Multi-label learning is a growing field in machine learning research. Many applications address instances that simultaneously belong to many categories, which cannot be disregarded if optimal results are desired. Among the ...

    • ML-k’sNN: Label Dependent k Values for Multi-Label k-Nearest Neighbor Rule 

      Cuevas-Muñoz, José Manuel; García Pedrajas, Nicolás (MDPI, 2023)
      Multi-label classification as a data mining task has recently attracted increasing interest from researchers. Many current data mining applications address problems with instances that belong to more than one category. ...

    • PARIS: Partial instance and training set selection. A new scalable approach to multi-label classification 

      García Pedrajas, Nicolás; Cuevas-Muñoz, José Manuel; Romero-del-Castillo, Juan A.; Haro García, Aída de (Elsevier, 2023)
      Multi-label classification has recently attracted research interest as a data mining task. Many current applications in data mining address problems that have instances belonging to more than one class. This requires the ...

    • SI(FS)2: Fast simultaneous instance and feature selection for datasets with many features 

      García Pedrajas, Nicolás; Romero-del-Castillo, Juan A.; Cerruela García, Gonzalo (Elsevier, 2021)
      Data reduction is becoming increasingly relevant due to the enormous amounts of data that are constantly being produced in many fields of research. Instance selection is one of the most widely used methods for this task. ...

    • SWFAD-IOT: Sistema de Apoyo a la Docencia en un Entorno IoT 

      Cerruela García, Gonzalo; García Pedrajas, Nicolás; Luque Ruiz, Irene; Gómez-Nieto, Miguel Ángel (UCOPress, 2019)
      El presente trabajo muestra el desarrollo e implementación de un sistema de apoyo a la docencia mediante la web física en un entorno del Internet de las Cosas (IoT). El sistema está orientado al desarrollo de actividades ...