Obtención Automática de Clases Genéricas a Través de una Operación de Parametrización. - Yania Crespo; Juan José Rodríguez; Francisco José García-Peñalvo; José Manuel Marqués Corral (JISBD, 1999)

Obtaining Generic Classes Automatically through a Parameterization Operator: A Focus on Constrained Genericity. - Yania Crespo; Juan José Rodríguez; José Manuel Marqués Corral (TOOLS (31), 1999)

Learning First Order Logic Time Series Classifiers. - Juan José Rodríguez; Carlos J. Alonso; Henrik Boström (ILP Work-in-progress reports, 2000)

Applying Boosting to Similarity Literals for Time Series Classification. - Juan J. Rodríguez Diez; Carlos Alonso González (Multiple Classifier Systems, 2000)

Learning First Order Logic Time Series Classifiers: Rules and Boosting. - Juan J. Rodríguez Diez; Carlos Alonso González; Henrik Boström (PKDD, 2000)

Time Series Classification by Boosting Interval Based Literals. - Carlos Alonso González; Juan J. Rodríguez Diez (Inteligencia Artif., 2000)

Learning Classification RBF Networks by Boosting. - Juan J. Rodríguez Diez; Carlos Alonso González (Multiple Classifier Systems, 2001)

Clasificación de Patrones Temporales en Sistemas Dinámicos mediante Boosting y Alineamiento Dinámico Temporal. - Juan J. Rodríguez Diez; Carlos J. Alonso; Q. Isaac Moro-Sancho (Computación y Sistemas, 2001)

Boosting interval based literals. - Juan J. Rodríguez Diez; Carlos Alonso González; Henrik Boström (Intell. Data Anal., 2001)

Learning microcontrollers with a CAI oriented multi-micro simulation environment. - Alfredo del Río; Juan José Rodríguez; Andrés A. Nogueiras Meléndez (IEEE Trans. Educ., 2001)

Enhancing Consistency Based Diagnosis with Machine Learning Techniques. - Carlos J. Alonso; Juan José Rodríguez; Belarmino Pulido Junquera (CAEPIA, 2003)

Rotation-Based Ensembles. - Juan José Rodríguez; Carlos J. Alonso (CAEPIA, 2003)

RBF Networks from Boosted Rules. - Juan José Rodríguez; Vanesa Paniego; Leticia Villar; Carlos J. Alonso (SNPD, 2003)

Interval and dynamic time warping-based decision trees. - Juan José Rodríguez; Carlos J. Alonso (SAC, 2004)

Support Vector Machines of Interval-based Features for Time Series Classification. - Juan José Rodríguez; Carlos J. Alonso (SGAI Conf., 2004)

Clasificación de Series: Máquinas de Vectores Soporte y Literales basados en Intervalos. - Juan José Rodríguez; Carlos J. Alonso (Inteligencia Artif., 2004)

Early Fault Classification in Dynamic Systems Using Case-Based Reasoning. - Aníbal Bregón; María Aránzazu Simón Hurtado; Juan José Rodríguez; Carlos J. Alonso; Belarmino Pulido Junquera; Q. Isaac Moro (CAEPIA, 2005)

Bias and Variance of Rotation-Based Ensembles. - Juan José Rodríguez; Carlos J. Alonso; Oscar J. Prieto (IWANN, 2005)

Support vector machines of interval-based features for time series classification. - Juan José Rodríguez; Carlos J. Alonso; José A. Maestro (Knowl. Based Syst., 2005)

Ensembles of Grafted Trees. - Juan José Rodríguez; Jesús Maudes (ECAI, 2006)

Rotation-based ensembles of RBF networks. - Juan José Rodríguez; Jesús Maudes; Carlos J. Alonso (ESANN, 2006)

Rotation Forest: A New Classifier Ensemble Method. - Juan José Rodríguez; Ludmila I. Kuncheva; Carlos J. Alonso (IEEE Trans. Pattern Anal. Mach. Intell., 2006)

Stacking Dynamic Time Warping for the Diagnosis of Dynamic Systems. - Carlos J. Alonso; Oscar J. Prieto; Juan José Rodríguez; Aníbal Bregón; Belarmino Pulido Junquera (CAEPIA, 2007)

Rotation Forest and Random Oracles: Two Classifier Ensemble Methods. - Juan J. Rodríguez Diez (CBMS, 2007)

An Experimental Study on Rotation Forest Ensembles. - Ludmila I. Kuncheva; Juan José Rodríguez (MCS, 2007)

Cascading for Nominal Data. - Jesús Maudes; Juan José Rodríguez; César Ignacio García-Osorio (MCS, 2007)

Naïve Bayes Ensembles with a Random Oracle. - Juan José Rodríguez; Ludmila I. Kuncheva (MCS, 2007)

Diagnosing scrapie in sheep: A classification experiment. - Ludmila I. Kuncheva; Victor J. del Rio Vilas; Juan J. Rodríguez Diez (Comput. Biol. Medicine, 2007)

Classifier Ensembles with a Random Linear Oracle. - Ludmila I. Kuncheva; Juan José Rodríguez (IEEE Trans. Knowl. Data Eng., 2007)

License Plate Number Recognition - New Heuristics and a Comparative Study of Classifiers. - César Ignacio García-Osorio; José-Francisco Díez-Pastor; Juan José Rodríguez; Jesús Maudes (ICINCO-RA (1), 2008)

Feature Selection and Classification for Small Gene Sets. - Gregor Stiglic; Juan J. Rodríguez Diez; Peter Kokol (PRIB, 2008)

Combining Online Classification Approaches for Changing Environments. - Juan José Rodríguez; Ludmila I. Kuncheva (SSPR/SPR, 2008)

Boosting recombined weak classifiers. - Juan José Rodríguez; Jesús Maudes (Pattern Recognit. Lett., 2008)

Disturbing Neighbors Ensembles for Linear SVM. - Jesús Maudes; Juan José Rodríguez; César Ignacio García-Osorio (MCS, 2009)

Disturbing Neighbors Diversity for Decision Forests. - Jesús Maudes; Juan J. Rodríguez Diez; César Ignacio García-Osorio (Applications of Supervised and Unsupervised Ensemble Methods, 2009)

Ensemble Methods and Model Based Diagnosis Using Possible Conflicts and System Decomposition. - Carlos J. Alonso-González; Juan José Rodríguez; Oscar J. Prieto; Belarmino Pulido Junquera (IEA/AIE (2), 2010)

Random Projections for SVM Ensembles. - Jesús Maudes; Juan José Rodríguez; César Ignacio García-Osorio; Carlos Pardo (IEA/AIE (2), 2010)

An Empirical Study of Multilayer Perceptron Ensembles for Regression Tasks. - Carlos Pardo; Juan José Rodríguez; César Ignacio García-Osorio; Jesús Maudes (IEA/AIE (2), 2010)

An Experimental Study on Ensembles of Functional Trees. - Juan José Rodríguez; César Ignacio García-Osorio; Jesús Maudes; José-Francisco Díez-Pastor (MCS, 2010)

Finding optimal classifiers for small feature sets in genomics and proteomics. - Gregor Stiglic; Juan José Rodríguez Diez; Peter Kokol (Neurocomputing, 2010)

Forests of nested dichotomies. - Juan José Rodríguez; César Ignacio García-Osorio; Jesús Maudes (Pattern Recognit. Lett., 2010)

Random Subspace Ensembles for fMRI Classification. - Ludmila I. Kuncheva; Juan José Rodríguez Diez; Catrin O. Plumpton; David E. J. Linden; Stephen J. Johnston (IEEE Trans. Medical Imaging, 2010)

Using Model Trees and Their Ensembles for Imbalanced Data. - Juan J. Rodríguez Diez; José-Francisco Díez-Pastor; César Ignacio García-Osorio; Pedro Santos (CAEPIA, 2011)

Using Ensembles of Regression Trees to Monitor Lubricating Oil Quality. - Andrés Bustillo; Alberto Villar; Eneko Gorritxategi; Susana Ferreiro; Juan José Rodríguez (IEA/AIE (1), 2011)

GRASP Forest: A New Ensemble Method for Trees. - José-Francisco Díez-Pastor; César Ignacio García-Osorio; Juan José Rodríguez; Andrés Bustillo (MCS, 2011)

Ensembles of Decision Trees for Imbalanced Data. - Juan José Rodríguez; José-Francisco Díez-Pastor; César Ignacio García-Osorio (MCS, 2011)

Random projections for linear SVM ensembles. - Jesús Maudes; Juan J. Rodríguez Diez; César Ignacio García-Osorio; Carlos Pardo (Appl. Intell., 2011)

Modelling of process parameters in laser polishing of steel components using ensembles of regression trees. - Andrés Bustillo; Eneko Ukar; Juan José Rodríguez; Aitzol Lamikiz (Int. J. Comput. Integr. Manuf., 2011)

Random Oracles for Regression Ensembles. - Carlos Pardo; Juan J. Rodríguez Diez; José-Francisco Díez-Pastor; César Ignacio García-Osorio (Ensembles in Machine Learning Applications, 2011)

Disturbing Neighbors Ensembles of Trees for Imbalanced Data. - Juan José Rodríguez Diez; José-Francisco Díez-Pastor; Jesús Maudes; César Ignacio García-Osorio (ICMLA (2), 2012)

Linear Projection Methods - An Experimental Study for Regression Problems. - Carlos Pardo-Aguilar; José-Francisco Díez-Pastor; Nicolás García-Pedrajas; Juan José Rodríguez Diez; César Ignacio García-Osorio (ICPRAM (1), 2012)

Classifier Ensemble Methods for Diagnosing COPD from Volatile Organic Compounds in Exhaled Air. - Ludmila I. Kuncheva; Juan José Rodríguez; Yasir Iftikhar Syed; Christopher O. Phillips; Keir Edward Lewis (Int. J. Knowl. Discov. Bioinform., 2012)

Random feature weights for decision tree ensemble construction. - Jesús Maudes; Juan J. Rodríguez Diez; César Ignacio García-Osorio; Nicolás García-Pedrajas (Inf. Fusion, 2012)

Supervised subspace projections for constructing ensembles of classifiers. - Nicolás García-Pedrajas; Jesús Manuel Maudes Raedo; César Ignacio García-Osorio; Juan José Rodríguez Diez (Inf. Sci., 2012)

Improvements in Modelling of Complex Manufacturing Processes Using Classification Techniques. - Pedro Santos; Jesús Maudes; Andrés Bustillo; Juan José Rodríguez (IEA/AIE, 2013)

Random Oracle Ensembles for Imbalanced Data. - Juan José Rodríguez Diez; José-Francisco Díez-Pastor; César Ignacio García-Osorio (MCS, 2013)

Rotation Forests for regression. - Carlos Pardo; José-Francisco Díez-Pastor; César Ignacio García-Osorio; Juan José Rodríguez Diez (Appl. Math. Comput., 2013)

Interval feature extraction for classification of event-related potentials (ERP) in EEG data analysis. - Ludmila I. Kuncheva; Juan José Rodríguez Diez (Prog. Artif. Intell., 2013)

Online breakage detection of multitooth tools using classifier ensembles for imbalanced data. - Andrés Bustillo; Juan José Rodríguez Diez (Int. J. Syst. Sci., 2014)

Tree ensemble construction using a GRASP-based heuristic and annealed randomness. - José-Francisco Díez-Pastor; César Ignacio García-Osorio; Juan José Rodríguez Diez (Inf. Fusion, 2014)

A weighted voting framework for classifiers ensembles. - Ludmila I. Kuncheva; Juan José Rodríguez Diez (Knowl. Inf. Syst., 2014)

An Experimental Study on Combining Binarization Techniques and Ensemble Methods of Decision Trees. - Juan José Rodríguez Diez; José-Francisco Díez-Pastor; Álvar Arnaiz-González; César Ignacio García-Osorio (MCS, 2015)

Diversity techniques improve the performance of the best imbalance learning ensembles. - José-Francisco Díez-Pastor; Juan José Rodríguez; César Ignacio García-Osorio; Ludmila I. Kuncheva (Inf. Sci., 2015)

Random Balance: Ensembles of variable priors classifiers for imbalanced data. - José-Francisco Díez-Pastor; Juan José Rodríguez Diez; César Ignacio García-Osorio; Ludmila I. Kuncheva (Knowl. Based Syst., 2015)

Stacking for multivariate time series classification. - Oscar J. Prieto; Carlos J. Alonso-González; Juan José Rodríguez Diez (Pattern Anal. Appl., 2015)

Instance selection for regression by discretization. - Álvar Arnaiz-González; José-Francisco Díez-Pastor; Juan José Rodríguez Diez; César Ignacio García-Osorio (Expert Syst. Appl., 2016)

Instance selection for regression: Adapting DROP. - Álvar Arnaiz-González; José-Francisco Díez-Pastor; Juan José Rodríguez Diez; César Ignacio García-Osorio (Neurocomputing, 2016)

Instance selection of linear complexity for big data. - Álvar Arnaiz-González; José-Francisco Díez-Pastor; Juan José Rodríguez; César Ignacio García-Osorio (Knowl. Based Syst., 2016)

Random feature weights for regression trees. - Álvar Arnaiz-González; José-Francisco Díez-Pastor; César Ignacio García-Osorio; Juan José Rodríguez Diez (Prog. Artif. Intell., 2016)

A decision-making tool based on decision trees for roughness prediction in face milling. - Juan José Rodríguez Diez; Guillem Quintana; Andrés Bustillo; Joaquim Ciurana (Int. J. Comput. Integr. Manuf., 2017)

Restricted set classification: Who is there? - Ludmila I. Kuncheva; Juan José Rodríguez Diez; Aaron S. Jackson (Pattern Recognit., 2017)

Local sets for multi-label instance selection. - Álvar Arnaiz-González; José-Francisco Díez-Pastor; Juan José Rodríguez Diez; César García-Osorio (Appl. Soft Comput., 2018)

Study of data transformation techniques for adapting single-label prototype selection algorithms to multi-label learning. - Álvar Arnaiz-González; José-Francisco Díez-Pastor; Juan José Rodríguez Diez; César García-Osorio (Expert Syst. Appl., 2018)

On feature selection protocols for very low-sample-size data. - Ludmila I. Kuncheva; Juan José Rodríguez Diez (Pattern Recognit., 2018)

Combining univariate approaches for ensemble change detection in multivariate data. - William J. Faithfull; Juan José Rodríguez Diez; Ludmila I. Kuncheva (Inf. Fusion, 2019)

Feature Selection from High-Dimensional Data with Very Low Sample Size: A Cautionary Tale. - Ludmila I. Kuncheva; Clare E. Matthews; Álvar Arnaiz-González; Juan José Rodríguez (CoRR, 2020)

An experimental evaluation of mixup regression forests. - Juan José Rodríguez; Mario Juez-Gil; Álvar Arnaiz-González; Ludmila I. Kuncheva (Expert Syst. Appl., 2020)

Random Balance ensembles for multiclass imbalance learning. - Juan José Rodríguez; José-Francisco Díez-Pastor; Álvar Arnaiz-González; Ludmila I. Kuncheva (Knowl. Based Syst., 2020)

Experimental evaluation of ensemble classifiers for imbalance in Big Data. - Mario Juez-Gil; Álvar Arnaiz-González; Juan José Rodríguez; César García-Osorio (Appl. Soft Comput., 2021)

Approx-SMOTE: Fast SMOTE for Big Data on Apache Spark. - Mario Juez-Gil; Álvar Arnaiz-González; Juan José Rodríguez; Carlos López Nozal; César García-Osorio (Neurocomputing, 2021)

Rotation Forest for Big Data. - Mario Juez-Gil; Álvar Arnaiz-González; Juan José Rodríguez Diez; Carlos López Nozal; César García-Osorio (Inf. Fusion, 2021)

Improve teaching with modalities and collaborative groups in an LMS: an analysis of monitoring using visualisation techniques. - María Consuelo Sáiz-Manzanares; Raúl Marticorena Sánchez; Juan José Rodríguez Diez; Sandra Rodríguez-Arribas; José-Francisco Díez-Pastor; Yi Peng Ji (J. Comput. High. Educ., 2021)

A Benchmark Database for Animal Re-Identification and Tracking. - Ludmila I. Kuncheva; Francis J. Williams; Samuel L. Hennessey; Juan José Rodríguez (IPAS, 2022)

Combination of Object Tracking and Object Detection for Animal Recognition. - Francis J. Williams; Ludmila I. Kuncheva; Juan José Rodríguez; Samuel L. Hennessey (IPAS, 2022)

When is resampling beneficial for feature selection with imbalanced wide data? - Ismael Ramos-Pérez; Álvar Arnaiz-González; Juan José Rodríguez; César García-Osorio (Expert Syst. Appl., 2022)

Rotation Forest for multi-target regression. - Juan José Rodríguez; Mario Juez-Gil; Carlos López Nozal; Álvar Arnaiz-González (Int. J. Mach. Learn. Cybern., 2022)

Correction to: Rotation Forest for multi-target regression. - Juan José Rodríguez; Mario Juez-Gil; Carlos López Nozal; Álvar Arnaiz-González (Int. J. Mach. Learn. Cybern., 2022)

An experiment on animal re-identification from video. - Ludmila I. Kuncheva; José Luis Garrido-Labrador; Ismael Ramos-Pérez; Samuel L. Hennessey; Juan José Rodríguez (Ecol. Informatics, 2023)

Evaluation of Semi-Supervised Machine Learning applied to Affective State Detection. - Íñigo Martin-Melero; Ana Serrano Mamolar; Juan J. Rodríguez Diez (PerCom Workshops, 2024)

Ensemble methods and semi-supervised learning for information fusion: A review and future research directions. - José Luis Garrido-Labrador; Ana Serrano Mamolar; Jesús Manuel Maudes Raedo; Juan José Rodríguez; César García-Osorio (Inf. Fusion, 2024)

Addressing data scarcity in protein fitness landscape analysis: A study on semi-supervised and deep transfer learning techniques. - José Antonio Barbero-Aparicio; Alicia Olivares-Gil; Juan José Rodríguez; César García-Osorio; José-Francisco Díez-Pastor (Inf. Fusion, 2024)

Semi-supervised diagnosis of wind-turbine gearbox misalignment and imbalance faults. - José Alberto Maestro-Prieto; José Miguel Ramírez-Sanz; Andrés Bustillo; Juan José Rodríguez Diez (Appl. Intell., 2024)

Semi-supervised classification with pairwise constraints: A case study on animal identification from video. - Ludmila I. Kuncheva; José Luis Garrido-Labrador; Ismael Ramos-Pérez; Samuel L. Hennessey; Juan José Rodríguez (Inf. Fusion, 2024)

SSLearn: A Semi-Supervised Learning library for Python. - José Luis Garrido-Labrador; Jesús Manuel Maudes Raedo; Juan José Rodríguez; César Ignacio García-Osorio (SoftwareX, 2025)

Semi-supervised prediction of protein fitness for data-driven protein engineering. - Alicia Olivares-Gil; José Antonio Barbero-Aparicio; Juan José Rodríguez; José-Francisco Díez-Pastor; César García-Osorio; Mehdi D. Davari (J. Cheminformatics, 2025)