Aida de Haro-García

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 12

Top Topics

Selection Algorithm

Instance Selection

Classification Models

Top Venues

Pattern Recognit.

IEEE Trans. Cybern.

Publications

Nicolás García-Pedrajas, José Manuel Cuevas-Muñoz, Gonzalo Cerruela García, Aida de Haro-García
Extensive experimental comparison among multilabel methods focused on ranking performance. Inf. Sci. 679 (2024)
Nicolás García-Pedrajas, José Manuel Cuevas-Muñoz, Gonzalo Cerruela García, Aida de Haro-García
A thorough experimental comparison of multilabel methods for classification performance. Pattern Recognit. 151 (2024)
Nicolás García-Pedrajas, José Manuel Cuevas-Muñoz, Aida de Haro-García
Evolutionary simultaneous under and oversampling of instances for dealing with class-imbalance datasets in multilabel problems. Appl. Soft Comput. 159 (2024)
Nicolás García-Pedrajas, José Manuel Cuevas-Muñoz, Juan Antonio Romero del Castillo, Aida de Haro-García
PARIS: Partial instance and training set selection. A new scalable approach to multi-label classification. Inf. Fusion 95 (2023)
Aida de Haro-García, José Pérez-Parras Toledano, Gonzalo Cerruela García, Nicolás García-Pedrajas
Grab'Em: A Novel Graph-Based Method for Combining Feature Subset Selectors. IEEE Trans. Cybern. 52 (5) (2022)
Javier Pérez-Rodríguez, Aida de Haro-García, Nicolás García-Pedrajas
Floating Search Methodology for Combining Classification Models for Site Recognition in DNA Sequences. IEEE ACM Trans. Comput. Biol. Bioinform. 18 (6) (2021)
Gonzalo Cerruela García, José Pérez-Parras Toledano, Aida de Haro-García, Nicolás García-Pedrajas
Influence of feature rankers in the construction of molecular activity prediction models. J. Comput. Aided Mol. Des. 34 (3) (2020)
Aida de Haro-García, Gonzalo Cerruela García, Nicolás García-Pedrajas
Ensembles of feature selectors for dealing with class-imbalanced datasets: A proposal and comparative study. Inf. Sci. 540 (2020)
Aida de Haro-García, Gonzalo Cerruela García, Nicolás García-Pedrajas
Instance selection based on boosting for instance-based learners. Pattern Recognit. 96 (2019)
Gonzalo Cerruela García, Aida de Haro-García, José Pérez-Parras Toledano, Nicolás García-Pedrajas
Improving the combination of results in the ensembles of prototype selectors. Neural Networks 118 (2019)
Javier Pérez-Rodríguez, Aida de Haro-García, Juan Antonio Romero del Castillo, Nicolás García-Pedrajas
A general framework for boosting feature subset selection algorithms. Inf. Fusion 44 (2018)
Aida de Haro-García, Javier Pérez-Rodríguez, Nicolás García-Pedrajas
Combining three strategies for evolutionary instance selection for instance-based learning. Swarm Evol. Comput. 42 (2018)
Nicolás García-Pedrajas, Aida de Haro-García, Javier Pérez-Rodríguez
A Scalable Memetic Algorithm for Simultaneous Instance and Feature Selection. Evol. Comput. 22 (1) (2014)
Nicolás García-Pedrajas, Aida de Haro-García
Boosting instance selection algorithms. Knowl. Based Syst. 67 (2014)
Nicolás García-Pedrajas, Javier Pérez-Rodríguez, Aida de Haro-García
OligoIS: Scalable Instance Selection for Class-Imbalanced Data Sets. IEEE Trans. Cybern. 43 (1) (2013)
Nicolás García-Pedrajas, Aida de Haro-García, Javier Pérez-Rodríguez
A scalable approach to simultaneous evolutionary instance and feature selection. Inf. Sci. 228 (2013)
Nicolás García-Pedrajas, Aida de Haro-García
Scaling up data mining algorithms: review and taxonomy. Prog. Artif. Intell. 1 (1) (2012)
Aida de Haro-García, Nicolás García-Pedrajas, Juan Antonio Romero del Castillo
Large scale instance selection by means of federal instance selection. Data Knowl. Eng. 75 (2012)
Aida de Haro-García, Javier Pérez-Rodríguez, Nicolás García-Pedrajas
A Comparison of Two Strategies for Scaling Up Instance Selection in Huge Datasets. CAEPIA (2011)
Javier Pérez-Rodríguez, Aida de Haro-García, Nicolás García-Pedrajas
Instance Selection for Class Imbalanced Problems by Means of Selecting Instances More than Once. CAEPIA (2011)
Aida de Haro-García, Javier Pérez-Rodríguez, Nicolás García-Pedrajas
Feature Selection for Translation Initiation Site Recognition. IEA/AIE (2) (2011)
Aida de Haro-García, Nicolás García-Pedrajas
A scalable method for instance selection for class-imbalance datasets. ISDA (2011)
Aida de Haro-García, Nicolás García-Pedrajas
Scaling Up Feature Selection by Means of Democratization. IEA/AIE (2) (2010)
Aida de Haro-García, Juan Antonio Romero del Castillo, Nicolás García-Pedrajas
Large Scale Instance Selection by Means of a Parallel Algorithm. IDEAL (2010)
César Ignacio García-Osorio, Aida de Haro-García, Nicolás García-Pedrajas
Democratic instance selection: A linear complexity instance selection algorithm based on classifier ensemble concepts. Artif. Intell. 174 (5-6) (2010)
Aida de Haro-García, Nicolás García-Pedrajas
A divide-and-conquer recursive approach for scaling up instance selection algorithms. Data Min. Knowl. Discov. 18 (3) (2009)