Ludmila I. Kuncheva

Ludmila Kuncheva

	2012
80		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 Recognition 45(6): 2101-2108 (2012)
	2011
79		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
78		Alberto Dainotti, Francesco Gargiulo, Ludmila I. Kuncheva, Antonio Pescapè, Carlo Sansone: Identification of Traffic Flows Hiding behind TCP Port 80. ICC 2010: 1-6
77		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
76		Gavin Brown, Ludmila I. Kuncheva: "Good" and "Bad" Diversity in Majority Vote Ensembles. MCS 2010: 124-133
75		Ludmila I. Kuncheva, Catrin O. Plumpton: Choosing Parameters for Random Subspace Ensembles for fMRI Classification. MCS 2010: 54-63
74		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. Med. Imaging 29(2): 531-542 (2010)
73		Robi Polikar, Joseph DePasquale, Hussein Syed Mohammed, Gavin Brown, Ludmila I. Kuncheva: Learn++.MF: A random subspace approach for the missing feature problem. Pattern Recognition 43(11): 3817-3832 (2010)
	2009
72		Indre, Ludmila I. Kuncheva: Determining the Training Window for Small Sample Size Classification with Concept Drift. ICDM Workshops 2009: 447-452
71		Francesco Gargiulo, Ludmila I. Kuncheva, Carlo Sansone: Network Protocol Verification by a Classifier Selection Ensemble. MCS 2009: 314-323
70		Ludmila I. Kuncheva, Indre Zliobaite: On the window size for classification in changing environments. Intell. Data Anal. 13(6): 861-872 (2009)
	2008
69		Ludmila I. Kuncheva, J. Salvador Sánchez: Nearest Neighbour Classifiers for Streaming Data with Delayed Labelling. ICDM 2008: 869-874
68		Ludmila I. Kuncheva, Indre Zliobaite: Linear Discriminant Classifier (LDC) for Streaming Data with Concept Drift. SSPR/SPR 2008: 4
67		Ludmila I. Kuncheva, Catrin O. Plumpton: Adaptive Learning Rate for Online Linear Discriminant Classifiers. SSPR/SPR 2008: 510-519
66		Juan José Rodríguez, Ludmila I. Kuncheva: Combining Online Classification Approaches for Changing Environments. SSPR/SPR 2008: 520-529
65		J. J. Charles, Ludmila I. Kuncheva, B. Wells, I. S. Lim: Background Segmentation in Microscopy Images. VISAPP (1) 2008: 139-145
64		J. J. Charles, Ludmila I. Kuncheva, B. Wells, I. S. Lim: Object segmentation within microscope images of palynofacies. Computers & Geosciences 34(6): 688-698 (2008)
63		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)
62		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 Recognition 41(10): 3010-3020 (2008)
61		Ludmila I. Kuncheva: Fuzzy classifiers. Scholarpedia 3(1): 2925 (2008)
	2007
60		Anand M. Narasimhamurthy, Ludmila I. Kuncheva: A framework for generating data to simulate changing environments. Artificial Intelligence and Applications 2007: 415-420
59		Ludmila I. Kuncheva: A stability index for feature selection. Artificial Intelligence and Applications 2007: 421-427
58		J. Salvador Sánchez, Ludmila I. Kuncheva: Data reduction using classifier ensembles. ESANN 2007: 379-384
57		Stefan Todorov Hadjitodorov, Ludmila I. Kuncheva: Selecting Diversifying Heuristics for Cluster Ensembles. MCS 2007: 200-209
56		Juan José Rodríguez, Ludmila I. Kuncheva: Naïve Bayes Ensembles with a Random Oracle. MCS 2007: 450-458
55		Ludmila I. Kuncheva, Juan José Rodríguez: An Experimental Study on Rotation Forest Ensembles. MCS 2007: 459-468
54		Ludmila I. Kuncheva, Victor J. del Rio Vilas, Juan J. Rodríguez Diez: Diagnosing scrapie in sheep: A classification experiment. Comp. in Bio. and Med. 37(8): 1194-1202 (2007)
53		Ludmila I. Kuncheva, Juan José Rodríguez: Classifier Ensembles with a Random Linear Oracle. IEEE Trans. Knowl. Data Eng. 19(4): 500-508 (2007)
	2006
52		J. J. Charles, Ludmila I. Kuncheva, B. Wells, I. S. Lim: An Evaluation Measure of Image Segmentation Based on Object Centres. ICIAR (1) 2006: 283-294
51		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)
50		Ludmila I. Kuncheva, Dmitry 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)
49		Stefan Todorov Hadjitodorov, Ludmila I. Kuncheva, Ludmila P. Todorova: Moderate diversity for better cluster ensembles. Information Fusion 7(3): 264-275 (2006)
48		Ludmila I. Kuncheva: On the optimality of Naïve Bayes with dependent binary features. Pattern Recognition Letters 27(7): 830-837 (2006)
47		Fernando Vilariño, Ludmila I. Kuncheva, Petia Radeva: ROC curves and video analysis optimization in intestinal capsule endoscopy. Pattern Recognition Letters 27(8): 875-881 (2006)
	2005
46		Ludmila I. Kuncheva: Diversity in multiple classifier systems. Information Fusion 6(1): 3-4 (2005)
45		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)
44		Ludmila I. Kuncheva: Using diversity measures for generating error-correcting output codes in classifier ensembles. Pattern Recognition Letters 26(1): 83-90 (2005)
	2004
43		Ludmila I. Kuncheva: Classifier Ensembles for Changing Environments. Multiple Classifier Systems 2004: 1-15
42		Ludmila I. Kuncheva, Stefan Todorov Hadjitodorov: Using diversity in cluster ensembles. SMC (2) 2004: 1214-1219
41		Christopher J. Whitaker, Ludmila I. Kuncheva, Peter D. Cockcroft: A Logodds Criterion for Selection of Diagnostic Tests. SSPR/SPR 2004: 574-582
40		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
39		Ludmila Kuncheva: That Elusive Diversity in Classifier Ensembles. IbPRIA 2003: 1126-1138
38		Ludmila I. Kuncheva: Error Bounds for Aggressive and Conservative AdaBoost. Multiple Classifier Systems 2003: 25-34
37		Ludmila I. Kuncheva, Christopher J. Whitaker: Measures of Diversity in Classifier Ensembles and Their Relationship with the Ensemble Accuracy. Machine Learning 51(2): 181-207 (2003)
36		Ludmila I. Kuncheva, Christopher J. Whitaker, Catherine A. Shipp: Limits on the majority vote accuracy in classifier fusion. Pattern Anal. Appl. 6(1): 22-31 (2003)
	2002
35		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
34		Ludmila I. Kuncheva, Christopher J. Whitaker: Using Diversity with Three Variants of Boosting: Aggressive, Conservative, and Inverse. Multiple Classifier Systems 2002: 81-90
33		Ludmila Kuncheva: A Theoretical Study on Six Classifier Fusion Strategies. IEEE Trans. Pattern Anal. Mach. Intell. 24(2): 281-286 (2002)
32		Ludmila I. Kuncheva: Switching between selection and fusion in combining classifiers: an experiment. IEEE Transactions on Systems, Man, and Cybernetics, Part B 32(2): 146-156 (2002)
31		Catherine A. Shipp, Ludmila Kuncheva: Relationships between combination methods and measures of diversity in combining classifiers. Information Fusion 3(2): 135-148 (2002)
30		Ludmila Kuncheva, Marina Skurichina, Robert P. W. Duin: An experimental study on diversity for bagging and boosting with linear classifiers. Information Fusion 3(4): 245-258 (2002)
29		Ludmila Kuncheva, Roumen K. Kounchev: Generating classifier outputs of fixed accuracy and diversity. Pattern Recognition Letters 23(5): 593-600 (2002)
	2001
28		Ludmila I. Kuncheva, Christopher J. Whitaker: Feature Subsets for Classifier Combination: An Enumerative Experiment. Multiple Classifier Systems 2001: 228-237
27		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
26		Ludmila Kuncheva: Using measures of similarity and inclusion for multiple classifier fusion by decision templates. Fuzzy Sets and Systems 122(3): 401-407 (2001)
25		James C. Bezdek, Ludmila Kuncheva: Nearest prototype classifier designs: An experimental study. Int. J. Intell. Syst. 16(12): 1445-1473 (2001)
24		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)
23		Ludmila Kuncheva, James C. Bezdek, Robert P. W. Duin: Decision templates for multiple classifier fusion: an experimental comparison. Pattern Recognition 34(2): 299-314 (2001)
	2000
22		Ludmila I. Kuncheva, Christopher J. Whitaker, Catherine A. Shipp, Robert P. W. Duin: Is Independence Good For Combining Classifiers? ICPR 2000: 2168-2171
21		Ludmila I. Kuncheva: Clustering-and-selection model for classifier combination. KES 2000: 185-188
20		A. S. Al-Zaidan, Ludmila I. Kuncheva: Selecting fuzzy connectives to represent heavy metal distribution in Liverpool Bay. KES 2000: 602-605
19		James C. Bezdek, Ludmila Kuncheva: Some Notes on Twenty One (21) Nearest Prototype Classifiers. SSPR/SPR 2000: 1-16
18		Ludmila Kuncheva, J. Wrench, Lakhmi C. Jain, A. S. Al-Zaidan: A fuzzy model of heavy metal loadings in Liverpool bay. Environmental Modelling and Software 15(2-3): 161-167 (2000)
17		Ludmila Kuncheva, Lakhmi C. Jain: Designing classifier fusion systems by genetic algorithms. IEEE Trans. Evolutionary Computation 4(4): 327-336 (2000)
16		Ludmila I. Kuncheva: How good are fuzzy If-Then classifiers? IEEE Transactions on Systems, Man, and Cybernetics, Part B 30(4): 501-509 (2000)
	1999
15		Ludmila Kuncheva, Friedrich Steimann: Fuzzy diagnosis. Artificial Intelligence in Medicine 16(2): 121-128 (1999)
14		Ludmila I. Kuncheva, James C. Bezdek: Presupervised and post-supervised prototype classifier design. IEEE Transactions on Neural Networks 10(5): 1142-1152 (1999)
13		Ludmila Kuncheva, Lakhmi C. Jain: Nearest neighbor classifier: Simultaneous editing and feature selection. Pattern Recognition Letters 20(11-13): 1149-1156 (1999)
	1998
12		Ludmila I. Kuncheva, James C. Bezdek: Nearest prototype classification: clustering, genetic algorithms, or random search? IEEE Transactions on Systems, Man, and Cybernetics, Part C 28(1): 160-164 (1998)
11		Ludmila I. Kuncheva, James C. Bezdek: An Integrated Framework for Generalized Nearest Prototype Classifier Design. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 6(5): 437-458 (1998)
	1997
10		Ludmila Kuncheva: Initializing of an RBF network by a genetic algorithm. Neurocomputing 14(3): 273-288 (1997)
9		Ludmila I. Kuncheva: Fitness functions in editing k-NN reference set by genetic algorithms. Pattern Recognition 30(6): 1041-1049 (1997)
	1995
8		Ludmila Kuncheva, Roumen K. Kounchev: On Feature Selection via Rough Sets. CAIP 1995: 625-630
7		Ludmila Kuncheva, Yordan K. Yotzov: Experimental Investigation on Editing for the k-NN Rule through a Genetic Algorithm. CAIP 1995: 766-771
6		Ludmila I. Kuncheva: Editing for the k-nearest neighbors rule by a genetic algorithm. Pattern Recognition Letters 16(8): 809-814 (1995)
	1993
5		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
4		Ludmila Kuncheva: Genetic Algorithm for Feature Selection for Parallel Classifiers. Inf. Process. Lett. 46(4): 163-168 (1993)
3		Ludmila I. Kuncheva: 'Change-glasses' approach in pattern recognition. Pattern Recognition Letters 14(8): 619-623 (1993)
	1992
2		Ludmila I. Kuncheva: A critical comment on the paper "designing of classification procedures with the use of equality and difference operators". Pattern Recognition 25(9): 1069-1071 (1992)
	1990
1		Vesselin Kissiov, Stefan Todorov Hadjitodorov, Ludmila I. Kuncheva: Using key features in pattern classification. Pattern Recognition Letters 11(1): 1-5 (1990)

Coauthor Index

1	A. S. Al-Zaidan	[18] [20]
2	Carlos J. Alonso (Carlos J. Alonso-González)	[51]
3	James C. Bezdek	[11] [12] [14] [19] [23] [25]
4	Gavin Brown	[73] [76]
5	J. J. Charles	[52] [64] [65]
6	Thomas Christy	[79]
7	Peter D. Cockcroft	[40] [41]
8	Alberto Dainotti	[78]
9	Joseph DePasquale	[73]
10	Juan José Rodríguez Diez (Juan J. Rodríguez Diez, Juan José Rodríguez)	[51] [53] [54] [55] [56] [66] [74]
11	Robert P. W. Duin	[22] [23] [30] [35]
12	Johann Gamper	[5]
13	Francesco Gargiulo	[71] [78]
14	Stefan Todorov Hadjitodorov	[1] [42] [49] [57]
15	Z. S. J. Hoare	[40]
16	Zoë Hoare	[63]
17	Indre	[72]
18	Lakhmi C. Jain	[13] [17] [18]
19	Stephen J. Johnston	[74] [77] [80]
20	Vesselin Kissiov	[1]
21	Roumen K. Kounchev	[8] [29]
22	I. S. Lim	[52] [64] [65]
23	David E. J. Linden	[74] [77]
24	Sa'ad P. Mansoor	[79]
25	Gian Luca Marcialis	[27]
26	David Masip	[45]
27	Hussein Syed Mohammed	[73]
28	Anand M. Narasimhamurthy	[60] [62]
29	Snezhana N. Neshkova	[5]
30	Nikolaas N. Oosterhof	[80]
31	Antonio Pescapè	[78]
32	Iestyn Pierce	[79]
33	Catrin O. Plumpton	[67] [74] [75] [77] [80]
34	Robi Polikar	[73]
35	Petia Radeva (Petia Radeva Ivanova)	[47]
36	Fabio Roli	[27]
37	J. Salvador Sánchez	[58] [69]
38	Carlo Sansone	[71] [78]
39	Catherine A. Shipp	[22] [27] [31] [36]
40	Marina Skurichina	[30] [35]
41	Friedrich Steimann	[15]
42	Ludmila P. Todorova	[49]
43	Dmitry Vetrov	[50]
44	Fernando Vilariño	[47]
45	Victor J. del Rio Vilas	[54]
46	Jordi Vitrià	[45]
47	B. Wells	[52] [64] [65]
48	Christopher J. Whitaker	[22] [28] [34] [36] [37] [40] [41] [62]
49	J. Wrench	[18]
50	Yordan K. Yotzov	[7]
51	Roumen Z. Zlatev	[5]
52	Indre Zliobaite	[68] [70]

Colors in the list of coauthors

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