default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDLudmila I. Kuncheva
Ludmila Kuncheva
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[j72]Ludmila I. Kuncheva, José Luis Garrido-Labrador
, Ismael Ramos-Pérez, Samuel L. Hennessey, Juan José Rodríguez:
Semi-supervised classification with pairwise constraints: A case study on animal identification from video. Inf. Fusion 104: 102188 (2024)- [c55]Samuel L. Hennessey, Francis J. Williams, Ludmila I. Kuncheva:
Hierarchical Vs Centroid-Based Constraint Clustering for Animal Video Data. IS 2024: 1-6 - [c54]Francis J. Williams, Samuel L. Hennessey, Ludmila I. Kuncheva, José-Francisco Díez-Pastor, Juan J. Rodriguez:
A Constrained Cluster Ensemble Using Hierarchical Clustering Methods. IS 2024: 1-6 - 2023
- [j71]Ludmila I. Kuncheva, José Luis Garrido-Labrador, Ismael Ramos-Pérez, Samuel L. Hennessey, Juan José Rodríguez:
An experiment on animal re-identification from video. Ecol. Informatics 74: 101994 (2023) - 2022
- [c53]Ludmila I. Kuncheva, Francis J. Williams, Samuel L. Hennessey, Juan José Rodríguez:
A Benchmark Database for Animal Re-Identification and Tracking. IPAS 2022: 1-6 - [c52]Francis J. Williams, Ludmila I. Kuncheva, Juan José Rodríguez, Samuel L. Hennessey:
Combination of Object Tracking and Object Detection for Animal Recognition. IPAS 2022: 1-6 - [i8]Ludmila Kuncheva, Francis J. Williams, Samuel L. Hennessey:
A Bibliographic View on Constrained Clustering. CoRR abs/2209.11125 (2022) - 2021
- [j70]Ludmila Kuncheva:
Animal reidentification using restricted set classification. Ecol. Informatics 62: 101225 (2021) - 2020
- [j69]Juan José Rodríguez, Mario Juez-Gil, Álvar Arnaiz-González, Ludmila I. Kuncheva:
An experimental evaluation of mixup regression forests. Expert Syst. Appl. 151: 113376 (2020) - [j68]Juan José Rodríguez, José-Francisco Díez-Pastor, Álvar Arnaiz-González, Ludmila I. Kuncheva:
Random Balance ensembles for multiclass imbalance learning. Knowl. Based Syst. 193: 105434 (2020) - [c51]Julian Zubek, Ludmila Kuncheva:
Abstraction and Generalization: Comparing Adaptive Models of Categorization. CogSci 2020 - [i7]Ludmila I. Kuncheva, Clare E. Matthews, Álvar Arnaiz-González, Juan José Rodríguez:
Feature Selection from High-Dimensional Data with Very Low Sample Size: A Cautionary Tale. CoRR abs/2008.12025 (2020)
2010 – 2019
- 2019
- [j67]William J. Faithfull, Juan José Rodríguez Diez, Ludmila I. Kuncheva:
Combining univariate approaches for ensemble change detection in multivariate data. Inf. Fusion 45: 202-214 (2019) - [j66]Clare E. Matthews, Ludmila I. Kuncheva, Paria Yousefi:
Classification and comparison of on-line video summarisation methods. Mach. Vis. Appl. 30(3): 507-518 (2019) - [j65]Ludmila I. Kuncheva, Álvar Arnaiz-González, José-Francisco Díez-Pastor, Iain A. D. Gunn:
Instance selection improves geometric mean accuracy: a study on imbalanced data classification. Prog. Artif. Intell. 8(2): 215-228 (2019) - [i6]Iain A. D. Gunn, Ludmila I. Kuncheva:
Bounds for the VC Dimension of 1NN Prototype Sets. CoRR abs/1902.02660 (2019) - 2018
- [j64]Iain A. D. Gunn, Álvar Arnaiz-González, Ludmila I. Kuncheva:
A taxonomic look at instance-based stream classifiers. Neurocomputing 286: 167-178 (2018) - [j63]Ludmila I. Kuncheva, Paria Yousefi, Jurandy Almeida:
Edited nearest neighbour for selecting keyframe summaries of egocentric videos. J. Vis. Commun. Image Represent. 52: 118-130 (2018) - [j62]Ludmila I. Kuncheva, Juan José Rodríguez Diez:
On feature selection protocols for very low-sample-size data. Pattern Recognit. 81: 660-673 (2018) - [j61]Ludmila I. Kuncheva, James H. V. Constance:
Restricted Set Classification with prior probabilities: A case study on chessboard recognition. Pattern Recognit. Lett. 111: 36-42 (2018) - [c50]Paria Yousefi, Ludmila I. Kuncheva:
Selective Keyframe Summarisation for Egocentric Videos Based on Semantic Concept Search. IPAS 2018: 19-24 - [c49]Paria Yousefi, Clare E. Matthews, Ludmila I. Kuncheva:
Budget-Constrained Online Video Summarisation of Egocentric Video Using Control Charts. ISVC 2018: 640-649 - [i5]Ludmila I. Kuncheva, Álvar Arnaiz-González, José-Francisco Díez-Pastor, Iain A. D. Gunn:
Instance Selection Improves Geometric Mean Accuracy: A Study on Imbalanced Data Classification. CoRR abs/1804.07155 (2018) - [i4]Julian Zubek, Ludmila Kuncheva:
Learning from Exemplars and Prototypes in Machine Learning and Psychology. CoRR abs/1806.01130 (2018) - 2017
- [j60]Ludmila I. Kuncheva, Juan José Rodríguez Diez, Aaron S. Jackson:
Restricted set classification: Who is there? Pattern Recognit. 63: 158-170 (2017) - [c48]Ludmila I. Kuncheva, Paria Yousefi, Jurandy Almeida:
Comparing keyframe summaries of egocentric videos: Closest-to-centroid baseline. IPTA 2017: 1-6 - [i3]Ludmila I. Kuncheva, Paria Yousefi, Iain A. D. Gunn:
On the Evaluation of Video Keyframe Summaries using User Ground Truth. CoRR abs/1712.06899 (2017) - [i2]Iain A. D. Gunn, Ludmila I. Kuncheva, Paria Yousefi:
Bipartite Graph Matching for Keyframe Summary Evaluation. CoRR abs/1712.06914 (2017) - 2016
- [c47]Ludmila Kuncheva:
Getting Lost in the Wealth of Classifier Ensembles? ICPRAM 2016: 7 - [c46]Ludmila I. Kuncheva, Iain A. D. Gunn:
A concept-drift perspective on prototype selection and generation. IJCNN 2016: 16-23 - 2015
- [j59]José-Francisco Díez-Pastor, Juan José Rodríguez, César Ignacio García-Osorio, Ludmila I. Kuncheva:
Diversity techniques improve the performance of the best imbalance learning ensembles. Inf. Sci. 325: 98-117 (2015) - [j58]José-Francisco Díez-Pastor, Juan José Rodríguez Diez, César Ignacio García-Osorio, Ludmila I. Kuncheva:
Random Balance: Ensembles of variable priors classifiers for imbalanced data. Knowl. Based Syst. 85: 96-111 (2015) - [c45]Ludmila I. Kuncheva, Mikel Galar:
Theoretical and Empirical Criteria for the Edited Nearest Neighbour Classifier. ICDM 2015: 817-822 - 2014
- [j57]Ludmila I. Kuncheva, Juan José Rodríguez Diez:
A weighted voting framework for classifiers ensembles. Knowl. Inf. Syst. 38(2): 259-275 (2014) - [j56]Ludmila I. Kuncheva, David Martínez-Rego, Kenneth S. L. Yuen, David E. J. Linden, Stephen J. Johnston:
A spatial discrepancy measure between voxel sets in brain imaging. Signal Image Video Process. 8(5): 913-922 (2014) - [j55]Javier Marín, David Vázquez, Antonio M. López, Jaume Amores, Ludmila I. Kuncheva:
Occlusion Handling via Random Subspace Classifiers for Human Detection. IEEE Trans. Cybern. 44(3): 342-354 (2014) - [j54]Ludmila I. Kuncheva, William J. Faithfull:
PCA Feature Extraction for Change Detection in Multidimensional Unlabeled Data. IEEE Trans. Neural Networks Learn. Syst. 25(1): 69-80 (2014) - [c44]Ludmila I. Kuncheva, Aaron S. Jackson:
Who Is Missing? A New Pattern Recognition Puzzle. S+SSPR 2014: 243-252 - [c43]William J. Faithfull, Ludmila I. Kuncheva:
On Optimum Thresholding of Multivariate Change Detectors. S+SSPR 2014: 364-373 - 2013
- [j53]Ludmila I. Kuncheva, Juan José Rodríguez Diez:
Interval feature extraction for classification of event-related potentials (ERP) in EEG data analysis. Prog. Artif. Intell. 2(1): 65-72 (2013) - [j52]Ludmila I. Kuncheva:
A Bound on Kappa-Error Diagrams for Analysis of Classifier Ensembles. IEEE Trans. Knowl. Data Eng. 25(3): 494-501 (2013) - [j51]Ludmila I. Kuncheva:
Change Detection in Streaming Multivariate Data Using Likelihood Detectors. IEEE Trans. Knowl. Data Eng. 25(5): 1175-1180 (2013) - 2012
- [j50]Ludmila I. Kuncheva, Juan José Rodríguez, Yasir Iftikhar Syed, Christopher O. Phillips, Keir Edward Lewis:
Classifier Ensemble Methods for Diagnosing COPD from Volatile Organic Compounds in Exhaled Air. Int. J. Knowl. Discov. Bioinform. 3(2): 1-15 (2012) - [j49]Catrin O. Plumpton, Ludmila I. Kuncheva, Nikolaas N. Oosterhof, Stephen J. Johnston:
Naive random subspace ensemble with linear classifiers for real-time classification of fMRI data. Pattern Recognit. 45(6): 2101-2108 (2012) - [c42]Ludmila I. Kuncheva, Christopher J. Smith, Yasir Iftikhar Syed, Christopher O. Phillips, Keir Edward Lewis:
Evaluation of Feature Ranking Ensembles for High-Dimensional Biomedical Data: A Case Study. ICDM Workshops 2012: 49-56 - [c41]Ludmila I. Kuncheva, William J. Faithfull:
PCA feature extraction for change detection in multidimensional unlabelled streaming data. ICPR 2012: 1140-1143 - [i1]Ludmila Kuncheva, Christopher J. Whitaker, Peter D. Cockcroft, Z. S. J. Hoare:
Pre-Selection of Independent Binary Features: An Application to Diagnosing Scrapie in Sheep. CoRR abs/1207.4141 (2012) - 2011
- [c40]Ludmila I. Kuncheva, Thomas Christy, Iestyn Pierce, Sa'ad P. Mansoor:
Multi-modal Biometric Emotion Recognition Using Classifier Ensembles. IEA/AIE (1) 2011: 317-326 - 2010
- [j48]Ludmila I. Kuncheva:
Full-class set classification using the Hungarian algorithm. Int. J. Mach. Learn. Cybern. 1(1-4): 53-61 (2010) - [j47]Robi Polikar, Joseph DePasquale, Hussein Syed Mohammed, Gavin Brown, Ludmila I. Kuncheva:
Learn++.MF: A random subspace approach for the missing feature problem. Pattern Recognit. 43(11): 3817-3832 (2010) - [j46]Ludmila I. Kuncheva, Juan José Rodríguez Diez, Catrin O. Plumpton, David E. J. Linden, Stephen J. Johnston:
Random Subspace Ensembles for fMRI Classification. IEEE Trans. Medical Imaging 29(2): 531-542 (2010) - [c39]Alberto Dainotti, Francesco Gargiulo, Ludmila I. Kuncheva, Antonio Pescapè, Carlo Sansone:
Identification of Traffic Flows Hiding behind TCP Port 80. ICC 2010: 1-6 - [c38]Catrin O. Plumpton, Ludmila I. Kuncheva, David E. J. Linden, Stephen J. Johnston:
On-Line fMRI Data Classification Using Linear and Ensemble Classifiers. ICPR 2010: 4312-4315 - [c37]Ludmila I. Kuncheva, Catrin O. Plumpton:
Choosing Parameters for Random Subspace Ensembles for fMRI Classification. MCS 2010: 54-63 - [c36]Gavin Brown, Ludmila I. Kuncheva:
"Good" and "Bad" Diversity in Majority Vote Ensembles. MCS 2010: 124-133
2000 – 2009
- 2009
- [j45]Ludmila I. Kuncheva, Indre Zliobaite:
On the window size for classification in changing environments. Intell. Data Anal. 13(6): 861-872 (2009) - [c35]Indre Zliobaite, Ludmila I. Kuncheva:
Determining the Training Window for Small Sample Size Classification with Concept Drift. ICDM Workshops 2009: 447-452 - [c34]Francesco Gargiulo, Ludmila I. Kuncheva, Carlo Sansone:
Network Protocol Verification by a Classifier Selection Ensemble. MCS 2009: 314-323 - 2008
- [j44]J. J. Charles, Ludmila I. Kuncheva, B. Wells, Ik Soo Lim:
Object segmentation within microscope images of palynofacies. Comput. Geosci. 34(6): 688-698 (2008) - [j43]Ludmila Kuncheva, Zoë Hoare:
Error-Dependency Relationships for the Naïve Bayes Classifier with Binary Features. IEEE Trans. Pattern Anal. Mach. Intell. 30(4): 735-740 (2008) - [j42]Ludmila I. Kuncheva, Christopher J. Whitaker, Anand M. Narasimhamurthy:
A case-study on naïve labelling for the nearest mean and the linear discriminant classifiers. Pattern Recognit. 41(10): 3010-3020 (2008) - [j41]Ludmila I. Kuncheva:
Fuzzy classifiers. Scholarpedia 3(1): 2925 (2008) - [c33]Ludmila I. Kuncheva, J. Salvador Sánchez:
Nearest Neighbour Classifiers for Streaming Data with Delayed Labelling. ICDM 2008: 869-874 - [c32]Ludmila I. Kuncheva, Indre Zliobaite:
Linear Discriminant Classifier (LDC) for Streaming Data with Concept Drift. SSPR/SPR 2008: 4 - [c31]Ludmila I. Kuncheva, Catrin O. Plumpton:
Adaptive Learning Rate for Online Linear Discriminant Classifiers. SSPR/SPR 2008: 510-519 - [c30]Juan José Rodríguez, Ludmila I. Kuncheva:
Combining Online Classification Approaches for Changing Environments. SSPR/SPR 2008: 520-529 - [c29]J. J. Charles, Ludmila I. Kuncheva, B. Wells, Ik Soo Lim:
Background Segmentation in Microscopy Images. VISAPP (1) 2008: 139-145 - 2007
- [j40]Ludmila I. Kuncheva, Victor J. del Rio Vilas, Juan J. Rodríguez Diez:
Diagnosing scrapie in sheep: A classification experiment. Comput. Biol. Medicine 37(8): 1194-1202 (2007) - [j39]Ludmila I. Kuncheva, Juan José Rodríguez:
Classifier Ensembles with a Random Linear Oracle. IEEE Trans. Knowl. Data Eng. 19(4): 500-508 (2007) - [c28]Anand M. Narasimhamurthy, Ludmila I. Kuncheva:
A framework for generating data to simulate changing environments. Artificial Intelligence and Applications 2007: 415-420 - [c27]Ludmila I. Kuncheva:
A stability index for feature selection. Artificial Intelligence and Applications 2007: 421-427 - [c26]J. Salvador Sánchez, Ludmila I. Kuncheva:
Data reduction using classifier ensembles. ESANN 2007: 379-384 - [c25]Stefan Todorov Hadjitodorov, Ludmila I. Kuncheva:
Selecting Diversifying Heuristics for Cluster Ensembles. MCS 2007: 200-209 - [c24]Juan José Rodríguez, Ludmila I. Kuncheva:
Naïve Bayes Ensembles with a Random Oracle. MCS 2007: 450-458 - [c23]Ludmila I. Kuncheva, Juan José Rodríguez:
An Experimental Study on Rotation Forest Ensembles. MCS 2007: 459-468 - 2006
- [j38]Stefan Todorov Hadjitodorov, Ludmila I. Kuncheva, Ludmila P. Todorova:
Moderate diversity for better cluster ensembles. Inf. Fusion 7(3): 264-275 (2006) - [j37]Juan José Rodríguez, Ludmila I. Kuncheva, Carlos J. Alonso:
Rotation Forest: A New Classifier Ensemble Method. IEEE Trans. Pattern Anal. Mach. Intell. 28(10): 1619-1630 (2006) - [j36]Ludmila I. Kuncheva, Dmitry P. Vetrov:
Evaluation of Stability of k-Means Cluster Ensembles with Respect to Random Initialization. IEEE Trans. Pattern Anal. Mach. Intell. 28(11): 1798-1808 (2006) - [j35]Ludmila I. Kuncheva:
On the optimality of Naïve Bayes with dependent binary features. Pattern Recognit. Lett. 27(7): 830-837 (2006) - [j34]Fernando Vilariño, Ludmila I. Kuncheva, Petia Radeva:
ROC curves and video analysis optimization in intestinal capsule endoscopy. Pattern Recognit. Lett. 27(8): 875-881 (2006) - [c22]Ludmila I. Kuncheva, Stefan Todorov Hadjitodorov, Ludmila P. Todorova:
Experimental Comparison of Cluster Ensemble Methods. FUSION 2006: 1-7 - [c21]J. J. Charles, Ludmila I. Kuncheva, B. Wells, Ik Soo Lim:
An Evaluation Measure of Image Segmentation Based on Object Centres. ICIAR (1) 2006: 283-294 - 2005
- [j33]Ludmila I. Kuncheva:
Diversity in multiple classifier systems. Inf. Fusion 6(1): 3-4 (2005) - [j32]David Masip, Ludmila Kuncheva, Jordi Vitrià:
An ensemble-based method for linear feature extraction for two-class problems. Pattern Anal. Appl. 8(3): 227-237 (2005) - [j31]Ludmila I. Kuncheva:
Using diversity measures for generating error-correcting output codes in classifier ensembles. Pattern Recognit. Lett. 26(1): 83-90 (2005) - 2004
- [b2]Ludmila I. Kuncheva:
Combining Pattern Classifiers: Methods and Algorithms. Wiley 2004, ISBN 9780471210788 - [c20]Ludmila I. Kuncheva:
Classifier Ensembles for Changing Environments. Multiple Classifier Systems 2004: 1-15 - [c19]Ludmila I. Kuncheva, Stefan Todorov Hadjitodorov:
Using diversity in cluster ensembles. SMC (2) 2004: 1214-1219 - [c18]Christopher J. Whitaker, Ludmila I. Kuncheva, Peter D. Cockcroft:
A Logodds Criterion for Selection of Diagnostic Tests. SSPR/SPR 2004: 574-582 - [c17]Ludmila I. Kuncheva, Christopher J. Whitaker, Peter D. Cockcroft, Z. S. J. Hoare:
Pre-Selection of Independent Binary Features: An Application to Diagnosing Scrapie in. UAI 2004: 325-332 - 2003
- [j30]Ludmila I. Kuncheva, Christopher J. Whitaker:
Measures of Diversity in Classifier Ensembles and Their Relationship with the Ensemble Accuracy. Mach. Learn. 51(2): 181-207 (2003) - [j29]Ludmila I. Kuncheva, Christopher J. Whitaker, Catherine A. Shipp, Robert P. W. Duin:
Limits on the majority vote accuracy in classifier fusion. Pattern Anal. Appl. 6(1): 22-31 (2003) - [j28]Ludmila I. Kuncheva:
"Fuzzy" versus "nonfuzzy" in combining classifiers designed by Boosting. IEEE Trans. Fuzzy Syst. 11(6): 729-741 (2003) - [c16]Ludmila Kuncheva:
That Elusive Diversity in Classifier Ensembles. IbPRIA 2003: 1126-1138 - [c15]Ludmila I. Kuncheva:
Error Bounds for Aggressive and Conservative AdaBoost. Multiple Classifier Systems 2003: 25-34 - 2002
- [j27]Catherine A. Shipp, Ludmila Kuncheva:
Relationships between combination methods and measures of diversity in combining classifiers. Inf. Fusion 3(2): 135-148 (2002) - [j26]Ludmila Kuncheva, Marina Skurichina, Robert P. W. Duin:
An experimental study on diversity for bagging and boosting with linear classifiers. Inf. Fusion 3(4): 245-258 (2002) - [j25]Ludmila Kuncheva:
A Theoretical Study on Six Classifier Fusion Strategies. IEEE Trans. Pattern Anal. Mach. Intell. 24(2): 281-286 (2002) - [j24]Ludmila Kuncheva, Roumen K. Kounchev:
Generating classifier outputs of fixed accuracy and diversity. Pattern Recognit. Lett. 23(5): 593-600 (2002) - [j23]Ludmila I. Kuncheva:
Switching between selection and fusion in combining classifiers: an experiment. IEEE Trans. Syst. Man Cybern. Part B 32(2): 146-156 (2002) - [c14]Marina Skurichina, Ludmila Kuncheva, Robert P. W. Duin:
Bagging and Boosting for the Nearest Mean Classifier: Effects of Sample Size on Diversity and Accuracy. Multiple Classifier Systems 2002: 62-71 - [c13]Ludmila I. Kuncheva, Christopher J. Whitaker:
Using Diversity with Three Variants of Boosting: Aggressive, Conservative, and Inverse. Multiple Classifier Systems 2002: 81-90 - 2001
- [j22]Ludmila Kuncheva:
Using measures of similarity and inclusion for multiple classifier fusion by decision templates. Fuzzy Sets Syst. 122(3): 401-407 (2001) - [j21]James C. Bezdek, Ludmila Kuncheva:
Nearest prototype classifier designs: An experimental study. Int. J. Intell. Syst. 16(12): 1445-1473 (2001) - [j20]Ludmila Kuncheva:
Fuzzy Logic with Engineering Applications, Timothy J. Ross, (Ed.); McGraw Hill, New York, 1995, pp 592, ISBN 0-07-053917-0. Neurocomputing 41(1-4): 187 (2001) - [j19]Ludmila Kuncheva, James C. Bezdek, Robert P. W. Duin:
Decision templates for multiple classifier fusion: an experimental comparison. Pattern Recognit. 34(2): 299-314 (2001) - [c12]Ludmila I. Kuncheva, Christopher J. Whitaker:
Feature Subsets for Classifier Combination: An Enumerative Experiment. Multiple Classifier Systems 2001: 228-237 - [c11]Ludmila I. Kuncheva, Fabio Roli, Gian Luca Marcialis, Catherine A. Shipp:
Complexity of Data Subsets Generated by the Random Subspace Method: An Experimental Investigation. Multiple Classifier Systems 2001: 349-358 - 2000
- [b1]Ludmila I. Kuncheva:
Fuzzy Classifier Design. Studies in Fuzziness and Soft Computing 49, Springer 2000, ISBN 978-3-7908-2472-8, pp. 1-270 - [j18]Ludmila Kuncheva, J. Wrench, Lakhmi C. Jain, Ameena S. Al-Zaidan:
A fuzzy model of heavy metal loadings in Liverpool bay. Environ. Model. Softw. 15(2-3): 161-167 (2000) - [j17]Ludmila Kuncheva, Lakhmi C. Jain:
Designing classifier fusion systems by genetic algorithms. IEEE Trans. Evol. Comput. 4(4): 327-336 (2000) - [j16]Ludmila I. Kuncheva:
How good are fuzzy If-Then classifiers? IEEE Trans. Syst. Man Cybern. Part B 30(4): 501-509 (2000) - [c10]Ludmila I. Kuncheva, Christopher J. Whitaker, Catherine A. Shipp, Robert P. W. Duin:
Is Independence Good For Combining Classifiers? ICPR 2000: 2168-2171 - [c9]Ludmila I. Kuncheva:
Clustering-and-selection model for classifier combination. KES 2000: 185-188 - [c8]Ameena S. Al-Zaidan, Ludmila I. Kuncheva:
Selecting fuzzy connectives to represent heavy metal distribution in Liverpool Bay. KES 2000: 602-605 - [c7]James C. Bezdek, Ludmila Kuncheva:
Some Notes on Twenty One (21) Nearest Prototype Classifiers. SSPR/SPR 2000: 1-16
1990 – 1999
- 1999
- [j15]Ludmila Kuncheva, Friedrich Steimann:
Fuzzy diagnosis. Artif. Intell. Medicine 16(2): 121-128 (1999) - [j14]Ludmila Kuncheva, Lakhmi C. Jain:
Nearest neighbor classifier: Simultaneous editing and feature selection. Pattern Recognit. Lett. 20(11-13): 1149-1156 (1999) - [j13]James C. Bezdek, James M. Keller, Raghu Krishnapuram, Ludmila I. Kuncheva, Nikhil R. Pal:
Will the real iris data please stand up? IEEE Trans. Fuzzy Syst. 7(3): 368-369 (1999) - [j12]Ludmila I. Kuncheva, James C. Bezdek:
Presupervised and post-supervised prototype classifier design. IEEE Trans. Neural Networks 10(5): 1142-1152 (1999) - 1998
- [j11]Ludmila I. Kuncheva, James C. Bezdek:
An Integrated Framework for Generalized Nearest Prototype Classifier Design. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 6(5): 437-458 (1998) - [j10]Ludmila I. Kuncheva, James C. Bezdek:
Nearest prototype classification: clustering, genetic algorithms, or random search? IEEE Trans. Syst. Man Cybern. Part C 28(1): 160-164 (1998) - 1997
- [j9]Ludmila Kuncheva:
Initializing of an RBF network by a genetic algorithm. Neurocomputing 14(3): 273-288 (1997) - [j8]Ludmila I. Kuncheva:
Fitness functions in editing k-NN reference set by genetic algorithms. Pattern Recognit. 30(6): 1041-1049 (1997) - 1996
- [j7]Ludmila I. Kuncheva, Raghu Krishnapuram:
A fuzzy consensus aggregation operator. Fuzzy Sets Syst. 79(3): 347-356 (1996) - [j6]Ludmila I. Kuncheva:
On the Equivalence between fuzzy and Statistical Classifiers. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 4(3): 245-254 (1996) - [c6]Ludmila Kuncheva, Stefan Todorov Hadjitodorov:
An RBF network with tunable function shape. ICPR 1996: 645-649 - 1995
- [j5]Ludmila I. Kuncheva:
Editing for the k-nearest neighbors rule by a genetic algorithm. Pattern Recognit. Lett. 16(8): 809-814 (1995) - [c5]Ludmila Kuncheva, Roumen K. Kounchev:
On Feature Selection via Rough Sets. CAIP 1995: 625-630 - [c4]Ludmila Kuncheva, Yordan K. Yotzov:
Experimental Investigation on Editing for the k-NN Rule through a Genetic Algorithm. CAIP 1995: 766-771 - 1994
- [c3]Ludmila I. Kuncheva, Sushmita Mitra:
A two-level classification scheme trained by a fuzzy neural network. ICPR (2) 1994: 467-469 - 1993
- [j4]Ludmila Kuncheva:
Genetic Algorithm for Feature Selection for Parallel Classifiers. Inf. Process. Lett. 46(4): 163-168 (1993) - [j3]Ludmila I. Kuncheva:
'Change-glasses' approach in pattern recognition. Pattern Recognit. Lett. 14(8): 619-623 (1993) - [c2]Ludmila Kuncheva, Roumen Z. Zlatev, Snezhana N. Neshkova, Johann Gamper:
A combination Scheme of Artificial Intelligence and Fuzzy Pattern Recognition in Medical Diagnosis. FLAI 1993: 157-164 - 1992
- [j2]Ludmila I. Kuncheva:
A critical comment on the paper "designing of classification procedures with the use of equality and difference operators". Pattern Recognit. 25(9): 1069-1071 (1992) - 1991
- [c1]Ludmila I. Kuncheva, Rumen Z. Zlatev, Vania Raicheva:
A Decision Making System in Aviation Medicine. MIE 1991: 418-422 - 1990
- [j1]Vesselin Kissiov, Stefan Todorov Hadjitodorov, Ludmila I. Kuncheva:
Using key features in pattern classification. Pattern Recognit. Lett. 11(1): 1-5 (1990)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-23 21:23 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
