José Ramón Cano De Amo
José Ramón Cano De Amo
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Prototype selection for nearest neighbor classification: Taxonomy and empirical study
S Garcia, J Derrac, J Cano, F Herrera
IEEE transactions on pattern analysis and machine intelligence 34 (3), 417-435, 2012
Using evolutionary algorithms as instance selection for data reduction in KDD: an experimental study
JR Cano, F Herrera, M Lozano
IEEE transactions on evolutionary computation 7 (6), 561-575, 2003
Replacement strategies to preserve useful diversity in steady-state genetic algorithms
M Lozano, F Herrera, JR Cano
Information sciences 178 (23), 4421-4433, 2008
A memetic algorithm for evolutionary prototype selection: A scaling up approach
S García, JR Cano, F Herrera
Pattern Recognition 41 (8), 2693-2709, 2008
Stratification for scaling up evolutionary prototype selection
JR Cano, F Herrera, M Lozano
Pattern Recognition Letters 26 (7), 953-963, 2005
Evolutionary stratified training set selection for extracting classification rules with trade off precision-interpretability
JR Cano, F Herrera, M Lozano
Data & Knowledge Engineering 60 (1), 90-108, 2007
On the combination of evolutionary algorithms and stratified strategies for training set selection in data mining
JR Cano, F Herrera, M Lozano
Applied Soft Computing 6 (3), 323-332, 2006
Monotonic classification: An overview on algorithms, performance measures and data sets
JR Cano, PA Gutiérrez, B Krawczyk, M Woźniak, S García
Neurocomputing 341, 168-182, 2019
Analysis of data complexity measures for classification
JR Cano
Expert systems with applications 40 (12), 4820-4831, 2013
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
Pattern Recognition Letters 29 (16), 2156-2164, 2008
Linguistic modeling with hierarchical systems of weighted linguistic rules
R Alcalá, JR Cano, O Cordón, F Herrera, P Villar, I Zwir
International Journal of Approximate Reasoning 32 (2-3), 187-215, 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
Journal of Intelligent & Fuzzy Systems 12 (3-4), 235-242, 2002
CommuniMents: A framework for detecting community based sentiments for events
MA Jarwar, RA Abbasi, M Mushtaq, O Maqbool, NR Aljohani, A Daud, ...
International Journal on Semantic Web and Information Systems (IJSWIS) 13 (2 …, 2017
Prototype selection to improve monotonic nearest neighbor
JR Cano, NR Aljohani, RA Abbasi, JS Alowidbi, S Garcia
Engineering Applications of Artificial Intelligence 60, 128-135, 2017
Diagnose effective evolutionary prototype selection using an overlapping measure
S García, JR Cano, E Bernado-Mansilla, F Herrera
International Journal of Pattern Recognition and Artificial Intelligence 23 …, 2009
A proposal of evolutionary prototype selection for class imbalance problems
S García, JR Cano, A Fernández, F Herrera
Intelligent Data Engineering and Automated Learning–IDEAL 2006: 7th …, 2006
Making CN2-SD subgroup discovery algorithm scalable to large size data sets using instance selection
JR Cano, F Herrera, M Lozano, S García
Expert Systems with Applications 35 (4), 1949-1965, 2008
A GRASP algorithm for clustering
JR Cano, O Cordón, F Herrera, L Sánchez
Advances in Artificial Intelligence—IBERAMIA 2002: 8th Ibero-American …, 2002
Replacement strategies to maintain useful diversity in steady-state genetic algorithms
M Lozano, F Herrera, JR Cano
Soft Computing: Methodologies and Applications, 85-96, 2005
DILS: constrained clustering through dual iterative local search
G González-Almagro, J Luengo, JR Cano, S García
Computers & Operations Research 121, 104979, 2020
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