L.
Kuncheva
Publications
2012
Kuncheva L.I., D. Martinez-Rego, Kenneth S. L. Yuen,
D. E. J. Linden, S. J. Johnston,
A Spatial Discrepancy Measure between Voxel Sets in Brain Imaging, Signal, Image and Video Processing, 2012
(in press, DOI:
10.1007/s11760-012-0326-0. The final publication is available at www.springerlink.com ).
pdf
2011
Kuncheva L.I., Change detection in streaming multivariate data using
likelihood detectors, IEEE
Transactions on Knowledge and Data Engineering, 2011 (in press). pdf
Kuncheva L.I., A bound on kappa-error diagrams for analysis of classifier
ensembles, IEEE
Transactions on Knowledge and Data Engineering, 2011 (in press). pdf
Plumpton C. O., L. I. Kuncheva, N. N. Oosterhof and
S. J. Johnston, Naive random
subspace ensemble with linear classifiers for real-time classification of fMRI
data, Pattern Recognition (in press).pdf
Kuncheva L.I., T. Christy, I.
Pierce and S. P. Mansoor. Multi-modal
Biometric Emotion Recognition using Classifier Ensembles, Proc 24th International Conference on
Industrial, Engineering & Other Applications of Applied Intelligent Systems
(IEA-AEI), NY, Lecture Notes in Computer Science, 2011, LNCS 6703, 317-326. pdf
2010
Kuncheva
L.I., Full-Class
Set Classification Using the Hungarian Algorithm, International Journal of Machine Learning and Cybernetics, 1 (1),
2010, 53-61, pdf.
[bib]
Polikar
R., J. DePasquale, H. S. Mohammed, G. Brown, L.I. Kuncheva, LEARN++.MF: A Random Subspace Approach for the Missing
Feature Problem, Pattern Recognition, 43, 2010, 3817-3832, pdf.
Kuncheva
L.I., J. J. Rodriguez, Classifier Ensembles for fMRI Data Analysis: An
Experiment, Magnetic Resonance Imaging, 28 (4), 2010, 583-593, pdf.
Plumpton
C. O., L. I. Kuncheva, L.I D. E. J. Linden and S. J. Johnston, On-line fMRI Data Classification Using Linear
and Ensemble Classifiers, Proc. ICPR 2010, Istanbul, Turkey, 2010, pdf.
Kuncheva
L.I., J. J. Rodriguez, C. O. Plumpton, D. E. J. Linden and S. J. Johnston, Random Subspace Ensembles for fMRI
Classification, IEEE
Transactions on Medical Imaging, 29 (2), 2010, 531-542, pdf. [bib]
Kuncheva
L.I. and C. O. Plumpton, Choosing
parameters for Random Subspace ensembles for fMRI classification, Proc. Multiple Classifier
Systems (MCS'10), Cairo ,
Egypt
Brown
G., L.I. Kuncheva, ''Good'' and ''bad'' diversity in majority vote ensembles, Proc. Multiple Classifier
Systems (MCS'10), Cairo ,
Egypt
Dainotti
A., F. Gargiulo, L.I. Kuncheva, A. Pescape and C. Sansone , Identification of traffic flows hiding behind
TCP port 80, Proc.
IEEE International Conference on Communications (ICC 2010), 2010, Cape Town , South
Africa
2009
Zliobaite
I. and L. I. Kuncheva, Determining
the Training Window for Small Sample Size Classification with Concept Drift, Proc. 1st International
Workshop on Transfer Mining (TM'09), In conjunction with the 2009 IEEE
International Conference on Data Mining (ICDM 2009), Dec 6-9, 2009, Miami,
Florida, USA, pdf, [bib].
Gargiulo
F., L. I. Kuncheva and C. Sansone. Network Protocol Verification by a Classifier Selection Ensemble, Proc. MCS 2009, Reykjavik
Kuncheva
L.I. and I. Zliobaite, On
the Window Size for Classification in Changing Environments, Intelligent Data Analysis, 13 (6), 2009, 314-323, pdf, [bib]
Charles J.J., L.I. Kuncheva, B. Wells and I.S. Lim, Stability of kerogen classification with regard
to image segmentation, Mathematical Geology, 41, 2009, 475-486, pdf. [bib]
Kuncheva
L.I., Using Control Charts for
Detecting Concept Change in Streaming Data, Technical Report, BCS-TR-001-2009,
School of Computer Science, Bangor University, UK, 2009, pdf. [bib]
2008
Kuncheva
L.I. Classifier Ensembles: Facts, Fiction, Faults and Future, 19th
International Conference on Pattern Recognition (ICPR), Tampa, Florida, 2008, slides (ppt), (plenary talk, not reviewed). [bib]
Kuncheva
L.I. and C.O. Plumpton, Adaptive learning rate
for online linear discriminant classifiers, Proc Joint IAPR
International Workshops on Structural and Syntactic Pattern Recognition and
Statistical Techniques in Pattern Recognition S+SSPR,
Rodriguez
J.J and L.I. Kuncheva, Combining online
classification approaches for changing environments, Proc Joint IAPR
International Workshops on Structural and Syntactic Pattern Recognition and
Statistical Techniques in Pattern Recognition S+SSPR, Orlando, Florida, USA
, 2008, 520-529, pdf [bib]
Kuncheva L.I. and J. S.
Sanchez, Nearest neighbour classifiers for streaming data with delayed
labelling, Proc. IEEE International Conference on Data Mining (ICDM08),
Kuncheva L.I. Classifier ensembles for handling concept
change in streaming data, SWIFT 2008,
Skovde, Sweden, 5/11/08, slides (pdf).
(invited talk, not reviewed)
Kuncheva L.I. Classifier ensembles for detecting concept
change in streaming data: Overview and perspectives, Proc. 2nd Workshop SUEMA 2008 (ECAI 2008),
Kuncheva L.I., C.J.
Whitaker and A. Narasimhamurthy, A case
study on naive labelling for the nearest mean and the linear discriminant
classifiers, Pattern Recognition,
41, 2008, 3010-3020, pdf.
Kuncheva L.I., J.J.
Charles, N. Miles, A. Collins, B. Wells and I.S. Lim, Automated kerogen classification in microscope images of dispersed
kerogen preparation, Mathematical
Geosciences, 40, 2008, 639-652, pdf.
Kuncheva L.I. and Z.S.J.
Hoare, Error-dependency relationships
for the Naive Bayes classifier with binary features, IEEE Transactions on Pattern Analysis and Machine Intelligence, 30 (4), 2008, 735-740, pdf.
Charles J.J., L.I. Kuncheva, B. Wells and I.S. Lim, Background segmentation in microscope images, Proc 3rd International Conference on
Computer Vision Theory and Applications VISAPP08, Madeira , Portugal
Charles J.J, L.I. Kuncheva, B. Wells and I.S. Lim, Object segmentation within microscope images of
palynofacies, Computers
& Geosciences, 34,
2008, 688-698, pdf.
Kuncheva L.I. Fuzzy classifiers,
Scholarpedia, 3(1):2925.
2007
***Rodriguez
J.J and L.I. Kuncheva, Time series classification: Decision forests and SVM on
interval and DTW features, Proc Workshop
no Time Series Classification, 13th International Conference on Knowledge
Discovery and Data mining, San
Jose , CA
***Winner of the 13th KDD
Challenge on Time Series Classification.
Kuncheva L.I. and J.J. Rodriguez, Classifier ensembles with a random linear oracle, IEEE Transactions on Knowledge and Data
Engineering, 19 (4),
2007, 500-508, pdf.
Kuncheva L.I., V.
del
Kuncheva L.I and J.J.
Rodriguez, An
experimental study on Rotation Forest ensembles, Proc 7th International Workshop
on Multiple Classifier Systems, MCS'07, Prague, Czech Republic, 2007, LNCS 4472,
459-468, pdf.
Rodriguez J.J and
L. I. Kuncheva, Naive Bayes ensembles with a random oracle, Proc 7th International Workshop
on Multiple Classifier Systems, MCS'07, Prague, Czech Republic, 2007, LNCS 4472,
450-458, pdf.
Hadjitodorov S. T. and L. I. Kuncheva, Selecting
diversifying heuristics for cluster ensembles, Proc 7th International Workshop
on Multiple Classifier Systems, MCS'07, Prague , Czech Republic
Sanchez J. S. and L.I. Kuncheva, Data reduction using classifier
ensembles, Proc.
11th European Symposium on Artificial Neural Networks, Bruges, Belgium,
2007, pdf.
Kuncheva L.I, A stability index for feature
selection, Proc. IASTED,
Artificial Intelligence and Applications, Innsbruck , Austria
Narasimhamurthy A., L.I. Kuncheva, A
framework for generating data to simulate changing environments, Proc. IASTED, Artificial Intelligence and
Applications, Innsbruck ,
Austria
2006
Charles J.J, L.I. Kuncheva, B. Wells, I.S. Lim, An evaluation measure of image segmentation
based on object centres, Proc. International Conference on Image Analysis and Recognition ICIAR,
2006, Portugal
Kuncheva L.I., D.P. Vetrov, Evaluation of stability of k-means cluster ensembles
with respect to random initialization, IEEE Transactions on Pattern Analysis and Machine Intelligence, 28 (11), 2006, 1798-1808, pdf □
Kuncheva L.I., S.T. Hadjitodorov, L.P. Todorova, Experimental comparison of cluster ensemble
methods, Proc
FUSION 2006, Florence ,
Italy
Rodriguez J.J, L.I. Kuncheva, C.J. Alonso,
Kuncheva L.I., On the optimality of Naive Bayes with dependent binary
features, Pattern
Recognition Letters, 27,
2006, 830-837, pdf.
Hadjitodorov S.T., L. I. Kuncheva, L. P. Todorova, Moderate diversity for better cluster
ensembles, Information Fusion, 7 (3), 2006, 264-275, pdf. □
Vilarino F., L.I. Kuncheva, P. Radeva, ROC curves and video analysis optimization in
intestinal capsule endoscopy, Pattern Recognition Letters, 27, 2006, 875-881, pdf. □
Kuncheva L.I., S.T. Hadjitodorov, Diversifying Heuristics for Cluster Ensembles, Technical Report, December 2006, pdf.
2005
Masip D., L.I. Kuncheva, J Vitria, An
ensemble-based method for linear feature extraction for two-class problems,
Pattern Analysis and Applications, 8, 2005, 227-237, pdf.
Kuncheva L.I., C.J. Whitaker, Pattern
Recognition, Encyclopedia of
Statistics in Behavioral Science, Wiley, Chichester, 2005, 3, 1532-1535, pdf.
Kuncheva L.I., Z.S.J. Hoare, P.D. Cockcroft, Selection of independent binary features using probabilities: An
example from veterinary medicine, Journal
of Modern Applied Statistical Methods, 4
(2), 2005, 528-537, pdf.
Kuncheva L.I., Using diversity measures for generating
error-correcting output codes in classifier ensembles, Pattern Recognition Letters, 26, 2005, 83-90, pdf.
Kuncheva L.I. Diversity in multiple classifier systems (Editorial),
Information Fusion, 6 (1), 2005, 3-4, pdf. □ [Special
issue on Diversity in Multiple Classifier System - table of contents]
2004
Kuncheva L.I. Combining
Pattern Classifiers. Methods and Algorithms, Wiley,
2004. □
Kuncheva L.I., S.T.
Hadjitodorov, Using diversity in cluster ensembles, Proc.
IEEE International Conference on Systems, Man and Cybernetics, The
Hague , The Netherlands
Kuncheva L.I., Classifier ensembles for changing environments, Proceedings 5th International Workshop on Multiple Classifier Systems, MCS2004, Cagliari, Italy, in F. Roli, J. Kittler and T. Windeatt (Eds.), Lecture Notes in Computer Science, Vol 3077, 2004, 1-15, pdf. □
Whitaker C.J., L.I.
Kuncheva, P.D. Cockcroft, A logodds criterion for selection of diagnostic
tests, Proc IAPR International Workshop on
Statistical Pattern Recognition, Lisbon, Portugal, 2004, 575-582, pdf.
Kuncheva L.I., P.D. Cockcroft,
C.J. Whitaker, Z.S. Hoare, Pre-selection of independent binary features:
An application to diagnosing scrapie in sheep, Proceedings
of 20th Conference on Uncertainty in Artificial Intelligence, Banff, Canada, 2004, 325-332, pdf.
2003
**Kuncheva L.I. `Fuzzy' vs `Non-fuzzy' in combining classifiers designed by boosting,
IEEE Transactions on Fuzzy Systems, 11
(6), 2003, 729-741, pdf. □
**Won the best paper award for 2006 in
IEEE Transactions on Fuzzy Systems.
Kuncheva L.I., C.J.
Kuncheva L.I., C.J. Whitaker. Measures of diversity in classifier ensembles, Machine Learning , 51 ,
2003, 181-207, pdf. □
Kuncheva L.I.. That
elusive diversity in classifier ensembles, Proc IbPRIA 2003, Mallorca, Spain, 2003, Lecture Notes in Computer Science, Springer-Verlag, LNCS 2652,
1126-1138, pdf. □
Kuncheva L.I.
Error bounds for aggressive and conservative AdaBoost, Proc MCS 2003,
Whitaker C.J., L.I. Kuncheva, Examining the relationship between majority vote accuracy and diversity
in bagging and boosting, Technical
Report, 2003, School of Informatics,
Grant A., D. Last, L. Kuncheva, N. Ward, Marine DGNSS availability and continuity,
The Journal of Navigation, 56, 2003, 353-369, pdf.
2002
Kuncheva L.I., M. Skurichina, R.P.W. Duin. An experimental study on diversity for bagging and boosting with linear classifiers, Information Fusion, 3 (2), 2002, 245-258, pdf. □
Shipp
*Kuncheva
L.I. Switching between selection and fusion
in combining classifiers: An experiment, IEEE Transactions on SMC, Part B, 32 (2), 2002, 146-156, pdf. □
*Won the Sage best Transaction paper
award for 2003 across IEEE Transactions
on SMC A, B and C.
Kuncheva L.I., R.K. Kountchev. Generating classifier outputs of fixed accuracy and diversity, Pattern Recognition Letters, 23, 2002, 593-600, pdf. □
Kuncheva L.I. A
theoretical study on six classifier fusion strategies, IEEE Transactions on PAMI, 24,
(2), 2002, 281-286, pdf. □
Shipp
L.I. Kuncheva and C.J. Whitaker. Using diversity with three variants of boosting: aggressive,
conservative and inverse, Proc. MCS 2002,
M. Skurichina, L.I. Kuncheva and
R.P.W. Duin. Bagging and Boosting for
the nearest mean classifier: Effects of sample size on diversity and accuracy,
Proc. MCS 2002,
2001
Kuncheva L.I., J. Wrench, L.C. Jain, and A. Al-Zaidan. A fuzzy model of heavy metal loadings in marine environment, in: Da Ruan, J. Kacprzyk and M. Fedrizzi (Eds.) Soft Computing for Risk Assessment and Management, Springer-Verlag group (Physica-Verlag, Heidelberg and New York), series `Studies in Fuzziness and Soft Computing', 2001, 355-371, pdf.
Kuncheva L.I. Combining
classifiers: Soft computing
solutions, in: S.K. Pal and A. Pal (Eds.) Pattern Recognition: From Classical to Modern Approaches, World Scientific
Publishing Co., Singapore, 2001, 427-452, pdf. □
Bezdek J.C., L.I. Kuncheva. Nearest prototype classifier designs: An experimental study, International
Journal of Intelligent Systems, 16 (12), 2001, 1445-1473, pdf. □
Kuncheva L.I. Using
measures of similarity and inclusion for multiple classifier fusion by decision
templates, Fuzzy Sets and Systems,
122, (3), 2001, 401-407, pdf. □
Kuncheva L.I., J.C. Bezdek and R.P.W.
Duin. Decision templates for multiple
classifier fusion, Pattern
Recognition, 34 (2), 2001,
299-314, pdf. □
Kuncheva L.I. 'Fuzzy' vs 'non-fuzzy' in combining classifiers: an experimental study,
Proc
LFA'01,
Kuncheva L.I., F. Roli, G.L.
Marcialis, C.A. Shipp, Complexity of
data subsets generated by the random subspace method: An experimental
investigation, MCS 2001, Cambridge, Lecture Notes in Computer Science,
LNCS 2096, 349-358, pdf.
Kuncheva L.I., C.J. Whitaker, Feature subsets for classifier combination:
An enumerative experiment, MCS 2001,
Shipp C.A., L.I. Kuncheva, Four measures of data complexity for
bootstrapping, splitting and feature sampling, Proc. CIMA 2001, Bangor,
June, 2001, 429-435, pdf.
Al-Zaidan A.S., L.I. Kuncheva, Using fuzzy similarities to analyze heavy
metal distribution in a marine environment, Proc. CIMA 2001,
Kuncheva L.I., C.J. Whitaker, Ten measures of diversity in classifier
ensembles: Limits for two classifiers, IEE Workshop on Intelligent
Sensor Processing,
2000
Kuncheva L.I, Fuzzy Classifier
Design, Springer-Verlag,
Kuncheva L.I., How
good are fuzzy if-then classifiers? IEEE
Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 30 (4), 2000, 501-509, pdf. □
Kuncheva L.I. and L.C. Jain, Designing classifier fusion systems by genetic algorithms, IEEE Transactions on Evolutionary Computation, 4 (4), 2000, 327-336, pdf. □
Kuncheva L.I., J. Wrench, L.C. Jain and A.S. Al-Zaidan, A fuzzy model of heavy metal loadings in
Liverpool bay, Environmental
Modelling and Software, 15 (2), 2000,
161-167, pdf.
Bezdek, J. C. and L.I. Kuncheva, Some
notes on 21 nearest prototype classifiers, Advances in Pattern Recognition,
Lecture Notes in Computer Science, 1876, eds. F. J. Ferri,
J. M. Inesta, A. Amin and P. Pudil, Springer, Berlin, 2000, 1-16.
Kuncheva L.I., C.J.
Kuncheva L.I. Cluster-and-selection
method for classifier combination, Proc. 4th International Conference on
Knowledge-Based Intelligent Engineering Systems & Allied Technologies
(KES'2000), Brighton, UK, 2000, 185-188, pdf.
□
Al-Zaidan, A.S., and L.I. Kuncheva. Selecting
fuzzy connectives to represent heavy metal distribution in Liverpool Bay, Proc.
4th International Conference on Knowledge-Based Intelligent Engineering Systems
& Allied Technologies (KES'2000),
1999
Kuncheva L.I. and L.C. Jain, Nearest
neighbor classifier: Simultaneous editing and feature selection, Pattern Recognition Letters, 20, 1999, 1149-1156, pdf. □
Bezdek J.C., J.M. Keller, R. Krishnapuram and L.I. Kuncheva, N.R. Pal, Will the real Iris data please stand up?, IEEE Transactions on Fuzzy Systems, 7(3), 1999, 368-369, pdf. □
Kuncheva L.I. and J.C. Bezdek, Presupervised
and postsupervised prototype classifier design, IEEE Transactions on Neural Networks, 10 (5), 1999, 1142-1152, pdf.
Kuncheva L.I. and F. Steimann, Fuzzy
Diagnosis (Editorial), Artificial
Intelligence in Medicine, 16(2), 1999,
121-128, pdf. □ [Special
issue on Fuzzy Diagnosis - table
of contents]
... 1998
Kuncheva L.I. and J.C. Bezdek, An integrated framework for generalized nearest prototype classifier design, International Journal of Uncertainty, Fuzziness and Knowledge-based Systems, 6 (5), 1998, 437-457, pdf.
Kuncheva L.I., J.C. Bezdek. Nearest
prototype classification: Clustering, genetic algorithms or random search? IEEE Transactions
on Systems, Man, and Cybernetics, C28 (1), 1998, 160-164, pdf. □
Kuncheva L.I., J.C. Bezdek and M.A. Sutton, On combining multiple classifiers by fuzzy templates, Proc NAFIPS'98, Pensacola, Florida, 1998, 193-197, pdf.
Kuncheva L.I. Fitness functions
in editing k-NN reference set by genetic algorithms, Pattern Recognition,
30, 1997, 1041-1049, pdf. □
Kuncheva L.I. Initializing an RBF
neural network by a genetic algorithm, Neurocomputing,
14, 1997, 273-288, pdf.
Kuncheva L.I. On the equivalence
between fuzzy and statistical classifiers, International Journal of Uncertainty, Fuzziness and
Knowledge-based Systems, 4 (3), 1998,
245-253, pdf.
Kuncheva L. Editing for the
k-nearest neighbors rule by a genetic algorithm, Pattern Recognition
Letters, Special Issue on Genetic Algorithms, 16, 1995, 809-814, pdf. □
Mitra S., L. Kuncheva. Improving
classification performance using fuzzy MLP and two-level selective partitioning
of the feature space, Fuzzy Sets and Systems, 70, 1995, 1-13,
pdf.
Kuncheva L.I. On combining
multiple classifiers, Proc. 7th International Conference on Information
Processing and Management of Uncertainty (IPMU'98),
Kuncheva L.I., J.C. Bezdek. Selection
of cluster prototypes from data by a genetic algorithm, Proc. 5th
European Congress on Intelligent Techniques and Soft Computing, Aachen, Germany,
1997, 1683-1688, pdf.
Kuncheva L.I., R. Krishnapuram. A
fuzzy consensus aggregation operator, Fuzzy
Sets and Systems, 79, 1996,
347-356, pdf.
Kuncheva L.I. Using degree of
consensus in two-level fuzzy pattern recognition, European Journal of Operational Research, 80, 1995, 365-370, pdf.
Kuncheva L.I.,
S. Mitra. A two-level classification scheme trained by a fuzzy neural network, Proc. 12 International Conference on Pattern
Recognition,
Mitra S., L.I. Kuncheva, Change-glasses
pattern classification with a fuzzy neural network, Proc 2nd International Conference on FUzzy Based Expert SysTems, FUBEST,
Sofia, Bulgaria, 1994, 29-32, pdf.
Kuncheva, L. I. Genetic
algorithm for feature selection for parallel classifiers, Information
Processing Letters, 46, 1993, 163-168, pdf,
□
Kuncheva, L. I. Fuzzy
rough sets: application to feature selection, Fuzzy Sets and Systems,
51, 1992, 147-153, pdf □
(h-index 38,Harzings
Publish-or-Perish; the publications contributing to that are marked with □)
Bangor
home page
Latest modification to this
page: 27/04/2012