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The ADMIRABLE  — Advanced Data MIning Research And (Business intelligence | Bioinformatics | Big data) LEarning — research group main aim is the development of new ensemble algorithms and the application of data mining, data visualization and pattern matching techniques to diverse fields as bioinformatics, time series classification and high dimensional data analysis.

Among the main achievements of the researchers of the group is the development of several new ensemble construction algorithms: Rotation Forest, Disturbing Neighbours, Nonlinear Boosting Projections, Random Balance, …, that have aroused the interest of the data mining community.

Its members are in close relationship with research groups of other universities, currently collaborating with groups from the universities of Córdoba and Valladolid. The researchers of the group have international connections too. They have done research works while visiting other universities such as Stockholm University in Sweden, University of Gales and West Scotland University in United Kingdom, and Tsinghua University in China.

Its research interests are among others: Artificial Intelligence, Data Mining, Multi-Dimensional Data Visualization, Ensemble Construction, Bioinformatics, Regressors Ensembles, Instance Selection, Feature Selection, Decision Trees.

The group is recognized by the regional government of Castile and Leon as a Consolidated Research Unit.

◉ Research lines

Ensemble Construction
This research line consists in designing new algorithms for construction strong classifiers from the combination of a set of weak classifiers.
Data Mining
Data mining has its roots in artificial intelligence and statistics, is the process of extracting hidden patterns from data solving forecasting, classification and clustering problems.
Instance and attribute selection
Reduce the number of instances and characteristics of a data set to accelerate processing without affecting the information obtained. Extend the methods used in the area of classification to others like regression and multi-label classification.
Big Data
Parallelization of data mining algorithms for their adaptation to the processing of large volumes of data.
Bioinformatics
Bioinformatics is the application of data mining and data analysis techniques to manage and analyse biological data. Common problems in bioinformatics include sequence aligning and gene prediction.
Data mining applications in Software Engineering
Reduce software maintenance costs by improving the quality of software processes and products through the application of data mining.
Applied Visualization Techniques
Designing new methods for the graphic representation of Multi-dimensional data in order to obtain a clearer idea of its structure, but also 3D modelling and Virtual Reality for the diffusion of Historical-Artistic and Archaeological Heritage

◉ Selected publications


The following is a short list of selected publications, to see the full list, go to the Publications page.

2022

Ramos-Pérez, Ismael; Arnaiz-González, Álvar; Rodríguez, Juan José; García-Osorio, César

When is resampling beneficial for feature selection with imbalanced wide data? Journal Article

Expert Systems with Applications, 188 , pp. 116015, 2022, ISSN: 0957-4174.

Abstract | Links | BibTeX

2021

Juez-Gil, Mario; Arnaiz-González, Álvar; Rodríguez, Juan José; López-Nozal, Carlos; García-Osorio, César

Rotation Forest for Big Data Journal Article

Information Fusion, 74 , pp. 39-49, 2021, ISSN: 1566-2535.

Abstract | Links | BibTeX

Rodríguez, Juan José; Juez-Gil, Mario; López-Nozal, Carlos; Arnaiz-González, Álvar

Rotation Forest for multi-target regression Journal Article

International Journal of Machine Learning and Cybernetics, 2021, ISSN: 1868-808X.

Abstract | Links | BibTeX

Díez-Pastor, José Francisco; del Val, Alain Gil; Veiga, Fernando; Bustillo, Andrés

High-accuracy classification of thread quality in tapping processes with ensembles of classifiers for imbalanced learning Journal Article

Measurement, 168 (108328), 2021, ISSN: 0263-2241.

Abstract | Links | BibTeX

2020

Juez-Gil, Mario; Saucedo-Dorantes, Juan José; Arnaiz-González, Álvar; López-Nozal, Carlos; García-Osorio, César; Lowe, David

Early and extremely early multi-label fault diagnosis in induction motors Journal Article

ISA Transactions, 106 , pp. 367-381, 2020, ISSN: 0019-0578.

Abstract | Links | BibTeX

Rodríguez, Juan José; Juez-Gil, Mario; Arnaiz-González, Álvar; Kuncheva, Ludmila I

An experimental evaluation of mixup regression forests Journal Article

Expert Systems with Applications, 151 (113376), 2020, ISSN: 0957-4174.

Abstract | Links | BibTeX

Rodríguez, Juan José; Díez-Pastor, José Francisco; Arnaiz-González, Álvar; Kuncheva, Ludmila I

Random Balance ensembles for multiclass imbalance learning Journal Article

Knowledge-Based Systems, 2020, ISSN: 0950-7051.

Abstract | Links | BibTeX

2019

Checa, David; Bustillo, Andrés

A review of immersive virtual reality serious games to enhance learning and training Journal Article

Multimedia Tools and Applications, pp. 1-21, 2019, ISSN: 1380-7501.

Abstract | Links | BibTeX

Kordos, Mirosław; Arnaiz-González, Álvar; García-Osorio, César

Evolutionary prototype selection for multi-output regression Journal Article

Neurocomputing, 358 , pp. 309-320, 2019, ISSN: 0925-2312.

Abstract | Links | BibTeX

Faithfull, William J; Rodríguez, Juan José; Kuncheva, Ludmila I

Combining univariate approaches for ensemble change detection in multivariate data Journal Article

Information Fusion, 45 , pp. 202-214, 2019, ISSN: 1566-2535.

Abstract | Links | BibTeX

2018

Kuncheva, Ludmila I; Rodríguez, Juan José

On feature selection protocols for very low-sample-size data Journal Article

Pattern Recognition, 81 , pp. 660-673, 2018, ISSN: 0031-3203.

Abstract | Links | BibTeX

Arnaiz-González, Álvar; Díez-Pastor, José Francisco; Rodríguez, Juan José; García-Osorio, César

Local sets for multi-label instance selection Journal Article

Applied Soft Computing, 68 , pp. 651-666, 2018, ISSN: 1568-4946.

Abstract | Links | BibTeX

2017

Kuncheva, Ludmila I; Rodríguez, Juan José; Jackson, Aaron S

Restricted set classification: Who is there? Journal Article

Pattern Recognition, 63 , pp. 158-170, 2017, ISSN: 0031-3203.

Abstract | Links | BibTeX

Sáiz-Manzanares, María Consuelo; Marticorena-Sánchez, Raúl; García-Osorio, César; Díez-Pastor, José Francisco

How Do B-Learning and Learning Patterns Influence Learning Outcomes? Journal Article

Frontiers in Psychology, 8 , pp. 745, 2017, ISSN: 1664-1078.

Abstract | Links | BibTeX

2016

Arnaiz-González, Álvar; Blachnik, Marcin; Kordos, Mirosław; García-Osorio, César

Fusion of instance selection methods in regression tasks Journal Article

Information Fusion, 30 , pp. 69 - 79, 2016, ISSN: 1566-2535.

Abstract | Links | BibTeX

Arnaiz-González, Álvar; Díez-Pastor, José Francisco; Rodríguez, Juan José; García-Osorio, César

Instance selection of linear complexity for big data Journal Article

Knowledge-Based Systems, 107 , pp. 83–95, 2016, ISSN: 0950-7051.

Abstract | Links | BibTeX

2015

Díez-Pastor, José Francisco; Rodríguez, Juan José; García-Osorio, César; Kuncheva, Ludmila I

Random Balance: Ensembles of variable priors classifiers for imbalanced data Journal Article

Knowledge-Based Systems, 85 , pp. 96-111, 2015, ISSN: 0950-7051.

Abstract | Links | BibTeX

Díez-Pastor, José Francisco; Rodríguez, Juan José; García-Osorio, César; Kuncheva, Ludmila I

Diversity techniques improve the performance of the best imbalance learning ensembles Journal Article

Information Sciences, 325 , pp. 98 - 117, 2015, ISSN: 0020-0255.

Abstract | Links | BibTeX

◉ Current projects

The following is our most recent funded research project, to see the full list of the funded projects in which we have participated, follow the link Research projects .

Métodos y Aplicaciones Industriales del Aprendizaje Semisupervisado
Referencia del proyecto: BU055P20
Entidad / Administración financiadora: Junta de Castilla y León, Fondo Europeo de Desarrollo Regional (FEDER)
Importe (en euros): 172.000,00€
Duración: Desde el 1 de noviembre del 2020 hasta el 30 de octubre del 2023
Nº de Investigadores: 8
Investigador principal: Dr. Juan José Rodríguez Diez
Descriptores:
ANEP: INF.- Ciencias de la Computación y Tec. Informát.
NABS: 13.2.- I+D de Ingeniería
FORD: 1.02.- Computación y Ciencias de la Información
UNESCO: 120304
ÁREA: Computer Science

CATEGORÍA: Computer Science Applications

◉ The team



Juan José Rodríguez Diez


César Ignacio García Osorio


Andrés Bustillo Iglesias


Jesús Maudes Raedo


Carlos López Nozal


Raúl Marticorena Sánchez


José Francisco Diez Pastor


Carlos Pardo Aguilar


Álvar Arnaiz González


Mario Juez Gil


Antonio Canepa Oneto


José A. Barbero Aparicio


César Represa Pérez


Pedro Latorre Carmona


David Checa Cruz


Francisco J. González Moya


José Luis Garrido Labrador


Kim Martinez García


Alicia Olivares Gil


José Miguel Ramírez Sanz


Ismael Ramos Pérez


Nicolás García Pedrajas


Rodolfo E. Haber Guerra


Colin Fyfe