José Ramón Cano de Amo

Contacto

jrcano@ujae5prwwFlaQn.es

Organismo

UJA

Researcher Profile

Total Desde 2019:
Citas Total: 2743 Desde 2019: 960
Índice H Total: 20 Desde 2019: 13
Índice i10 Total: 30 Desde 2019: 18

Publicaciones (56)

Título Autores Año
Semi-Supervised Constrained Clustering: An In-Depth Overview, Ranked Taxonomy and Future Research Directions G González-Almagro, D Peralta, E De Poorter, JR Cano, S García. 2023
Semi-supervised Clustering with Two Types of Background Knowledge: Fusing Pairwise Constraints and Monotonicity Constraints G González-Almagro, JL Suárez, P Sánchez-Bermejo, JR Cano, S García. 2023
Monotonic Constrained Clustering: A First Approach G González-Almagro, PS Bermejo, JL Suarez, JR Cano, S García. 2022
Enhancing instance-level constrained clustering through differential evolution G González-Almagro, J Luengo, JR Cano, S García. 2021
ME-MEOA/DCC: Multiobjective constrained clustering through decomposition-based memetic elitism G González-Almagro, A Rosales-Pérez, J Luengo, JR Cano, S García. 2021
3SHACC: Three Stages Hybrid Agglomerative Constrained Clustering G González-Almagro, JL Suarez, J Luengo, JR Cano, S García. 2021
Similarity-based and Iterative Label Noise Filters for Monotonic Classification JR Cano, J Luengo, S García. 2020
DILS: constrained clustering through Dual Iterative Local Search G González-Almagro, J Luengo, JR Cano, S García. 2020
ProLSFEO-LDL: Prototype Selection and Label-Specific Feature Evolutionary Optimization for Label Distribution Learning M González, JR Cano, S García. 2020
Improving constrained clustering via decomposition-based multiobjective optimization with memetic elitism G González-Almagro, A Rosales-Pérez, J Luengo, JR Cano, S García. 2020
Synthetic Sample Generation for Label Distribution Learning M González, J Luengo, JR Cano, S García. 2020
Decomposition-Fusion for Label Distribution Learning M González, G González-Almagro, I Triguero, JR Cano, S García. 2020
Agglomerative Constrained Clustering Through Similarity and Distance Recalculation G González-Almagro, JL Suarez, J Luengo, JR Cano, S García. 2020
Similarity-based and Iterative Label Noise Filters for Monotonic Classification. JR Cano, J Luengo, S García. 2020
Label noise filtering techniques to improve monotonic classification JR Cano, J Luengo, S García. 2019
Monotonic classification: An overview on algorithms, performance measures and data sets JR Cano, PA Gutiérrez, B Krawczyk, M Woźniak, S García. 2019
A First Attempt on Monotonic Training Set Selection JR Cano, S García. 2018
Credal C4. 5 with Refinement of Parameters CJ Mantas, J Abellán, JG Castellano, JR Cano, S Moral. 2018
CommuniMents: A framework for detecting community based sentiments for events MA Jarwar, RA Abbasi, M Mushtaq, O Maqbool, NR Aljohani, A Daud, .... 2017
Prototype selection to improve monotonic nearest neighbor JR Cano, NR Aljohani, RA Abbasi, JS Alowidbi, S Garcia. 2017
MoNGEL: monotonic nested generalized exemplar learning J García, HM Fardoun, DM Alghazzawi, JR Cano, S García. 2017
Training set selection for monotonic ordinal classification JR Cano, S García. 2017
Hyperrectangles selection for monotonic classification by using evolutionary algorithms J García, AM AlBar, NR Aljohani, JR Cano, S García. 2016
A Nearest Hyperrectangle Monotonic Learning Method J García, JR Cano, S García. 2016
Analysis of data complexity measures for classification JR Cano. 2013
Predictive–collaborative model as recovery and validation tool. Case of study: Psychiatric emergency department decision support JR Cano. 2012
Prototype selection for nearest neighbor classification: Taxonomy and empirical study S Garcia, J Derrac, JR Cano, F Herrera. 2011
Prototype selection for nearest neighbor classification: Survey of methods S Garcıa, J Derrac, JR Cano, F Herrera. 2010
A Review on Evolutionary Prototype Selection: An Empirical Study of Performance and Efficiency S García, JR Cano, F Herrera. 2010
Modelo predictivo colaborativo de apoyo al diagnostico en servicio de urgencias psiquiatricas JR Cano, MJ del Jesús, P González, JJ Aguilera, AG López, F Herrera, .... 2009
Diagnose effective evolutionary prototype selection using an overlapping measure S Garcia, JR Cano, E Bernado-Mansilla, F Herrera. 2009
A memetic algorithm for evolutionary prototype selection: A scaling up approach S García, JR Cano, F Herrera. 2008
Replacement strategies to preserve useful diversity in steady-state genetic algorithms M Lozano, F Herrera, JR Cano. 2008
Subgroup discover in large size data sets preprocessed using stratified instance selection for increasing the presence of minority classes JR Cano, S García, F Herrera. 2008
Making CN2-SD subgroup discovery algorithm scalable to large size data sets using instance selection JR Cano, F Herrera, M Lozano, S García. 2008
Evolutionary stratified training set selection for extracting classification rules with trade off precision-interpretability JR Cano, F Herrera, M Lozano. 2007
Un algoritmo memético para selección de prototipos: Una propuesta eficiente para problemas de tamano medio S Garcıa, JR Cano, F Herrera. 2007
Analysis of evolutionary prototipe selection by means of a data complexity measure based on class separability JR Cano, S García, F Herrera, EB Mansilla. 2007
On the combination of evolutionary algorithms and stratified strategies for training set selection in data mining JR Cano, F Herrera, M Lozano. 2006
A proposal of evolutionary prototype selection for class imbalance problems S García, JR Cano, A Fernández, F Herrera. 2006
Técnicas de reducción de datos en KDD. El uso de Algoritmos Evolutivos para la Selección de Instancias F Herrera, JR Cano. 2006
Incorporating knowledge in evolutionary prototype selection S García, JR Cano, F Herrera. 2006
Técnicas de reducción de datos en KDD F Herrera, J Cano. 2006
2. Strategies for Scaling Up Evolutionary Instance Reduction Algorithms for Data Mining JR Cano, F Herrera, M Lozano. 2006
Stratification for scaling up evolutionary prototype selection JR Cano, F Herrera, M Lozano. 2005
Replacement strategies to maintain useful diversity in steady-state genetic algorithms M Lozano, F Herrera, JR Cano. 2005
A study on the combination of evolutionary algorithms and stratified strategies for training set selection in data mining JR Cano, F Herrera, M Lozano. 2005
Strategies for scaling up evolutionary instance reduction algorithms for data mining JR Cano, F Herrera, M Lozano. 2005
Instance selection using evolutionary algorithms: an experimental study JR Cano, F Herrera, M Lozano. 2005
Extracción de modelos predictivos e interpretables en conjuntos de datos de tamaño grande mediante la selección de conjuntos de entrenamiento JR Cano, F Herrera, M Lozano. 2005
Extración de modelos predictivos e interpretables en conjuntos de datos tamaño grande mediante la selección de conjuntos de entrenamiento R Cano, F Herrera, M Lozano. 2005
Insomnio: enfoque diagnòstico y terapéutico J Cano, J Garcìa. 2005
Reducción de datos basada en Selección Evolutiva de Instancias para Minerıa de Datos JRC de Amo. 2004
Evolutionary stratified instance selection applied to training set selection for extracting high precise-interpretable classification rules JR Cano, F Herrera, M Lozano. 2004
Linguistic modeling with hierarchical systems of weighted linguistic rules R Alcalá, JR Cano, O Cordón, F Herrera, P Villar, I Zwir. 2003
Using evolutionary algorithms as instance selection for data reduction in KDD: an experimental study JR Cano, F Herrera, M Lozano. 2003
A greedy randomized adaptive search procedure applied to the clustering problem as an initialization process using K-Means as a local search procedure JR Cano, O Cordón, F Herrera, L Sánchez. 2002
A GRASP algorithm for clustering JR Cano, O Cordón, F Herrera, L Sánchez. 2002
Tumor necrosis factor-alpha: a mediator in the pathogenesis of cardiac insufficiency EG Herrera, AG Cubillos, SJ Stetson, RN Cano, FF Herrera, JB Durand, .... 1999
Heterotopic heart transplantation: 13-year experience at the Methodist Hospital of the Baylor Medical College EG Herrera, GP Noon, JB Durand, SJ Stetson, S Zylicz, L Johnson, .... 1999
Preliminary results in the study of chromosome races found in Ameles abjecta (Amelinae, Mantodea) JC Orozco, M Espejo, J Cano. 1983

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