1. Published

   Evaluation of stability of k-means cluster ensembles with respect to random initialization

   Kuncheva, L. I. & Vetrov, D. P., 1 Nov 2006, In: IEEE Transactions on Pattern Analysis and Machine Intelligence. 28, 11, p. 1798-1808

   Research output: Contribution to journal › Article › peer-review

2. Published

   Pre-selection of independent binary features: An application to diagnosing scrapie in sheep

   Kuncheva, L. I., Cockcroft, P. D., Whitaker, C. J. & Hoare, Z., 1 Jan 2004, p. 325-332.

   Research output: Contribution to conference › Paper

3. Published

   On the window size for classification in changing environments.

   Kuncheva, L. I. & Žliobaitė, I., 25 Nov 2009, In: Intelligent Data Analysis. 13, 6, p. 861-872

   Research output: Contribution to journal › Article › peer-review

4. Published

   A benchmark database for animal re-identification and tracking

   Kuncheva, L., Hennessey, S., Williams, F. & Rodriguez, J., 6 Dec 2023, Proc. of the Fifth IEEE International Conference on Image Processing, Applications and Systems (IPAS). IEEE

   Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5. Published

   A case-study on naive labelling for the nearest mean and the linear discriminant classifiers

   Kuncheva, L. I., Whitaker, C. J. & Narasimhamurthy, A., 1 Oct 2008, In: Pattern Recognition. 41, 10, p. 3010-3020

   Research output: Contribution to journal › Article › peer-review

6. Published

   Automated kerogen classification in microscope images of dispersed kerogen preparation

   Kuncheva, L. I., Charles, J. J., Miles, N., Collins, A., Wells, B. & Lim, I. S., 1 Aug 2008, In: Mathematical Geosciences. 40, 6, p. 639-652

   Research output: Contribution to journal › Article › peer-review

7. Published

   A spatial discrepancy measure between voxel sets in brain imaging

   Kuncheva, L. I., Martinez-Rego, D., Yuen, K. S., Linden, D. E. & Johnston, S. J., 15 May 2014, In: Signal, Image and Video Processing. 8, 5, p. 913-922

   Research output: Contribution to journal › Article › peer-review

8. Published

   Occlusion Handling via Random Subspace Classifiers for Human Detection

   Kuncheva, L. I., Marin, J., Vazquez, D., Lopez, A. M., Amores, J. & Kuncheva L.I., [. V., 6 May 2013, In: IEEE Transactions on Cybernetics. 44, 3, p. 342-354

   Research output: Contribution to journal › Article › peer-review

9. Published

   Classifier ensembles for changing environments.

   Kuncheva, L. I., 1 Jan 2004, p. 1-15.

   Research output: Contribution to conference › Paper

10. Published

    Interval feature extraction for classification of event-related potentials (ERP) in EEG data analysis

    Kuncheva, L. I. & Rodriguez, J. J., 25 Dec 2012, In: Progress in Artificial Intelligence. 2, 1, p. 65-72

    Research output: Contribution to journal › Article › peer-review

11. Published

    Switching between selection and fusion in combining classifiers: An experiment

    Kuncheva, L. I., 1 Apr 2002, In: IEEE Transactions on SMC, Part B. 32, 2, p. 146-156

    Research output: Contribution to journal › Article › peer-review

12. Published

    Experimental comparison of cluster ensemble methods.

    Kuncheva, L. I., Hadjitodorov, S. T. & Todorova, L. P., 1 Jan 2006.

    Research output: Contribution to conference › Paper

13. Published

    Decision templates for multiple classifier fusion: an experimental comparison.

    Kuncheva, L. I., Bezdek, J. C. & Duin, R. P., 1 Feb 2001, In: Pattern Recognition. 34, 2, p. 299-314

    Research output: Contribution to journal › Article › peer-review

14. Published

    Combining classifiers: Soft computing solutions.

    Kuncheva, L. I., Pal, S. K. (Editor) & Pal, A. (Editor), 1 Jan 2001, Pattern Recognition: From Classical to Modern Approaches. 2001 ed. Unknown, p. 427-452

    Research output: Chapter in Book/Report/Conference proceeding › Chapter

15. Published

    Complexity of data subsets generated by the random subspace method: An experimental investigation

    Kuncheva, L. I., Roli, F., Marcialis, G. L. & Shipp, C. A., 1 Jan 2001, p. 349-358.

    Research output: Contribution to conference › Paper

16. Published

    Error bounds for aggressive and conservative AdaBoost.

    Kuncheva, L. I., 1 Jan 2003, p. 25-34.

    Research output: Contribution to conference › Paper

17. Published

    Animal Reidentification using Restricted Set Classification

    Kuncheva, L., May 2021, In: Ecological Informatics. 62, 101225.

    Research output: Contribution to journal › Article › peer-review

18. Published

    Full-class set classification using the Hungarian algorithm.

    Kuncheva, L. I., 1 Dec 2010, In: International Journal of Machine Learning and Cybernetics. 1, 1-4, p. 53-61

    Research output: Contribution to journal › Article › peer-review

19. Published

    A Bound on Kappa-Error Diagrams for Analysis of Classifier Ensembles

    Kuncheva, L. I., 1 Mar 2013, In: IEEE Transactions on Knowledge and Data Engineering. 25, 3, p. 494-501

    Research output: Contribution to journal › Article › peer-review

20. Published

    Semi-Supervised Classification With Pairwise Constraints: A Case Study on Animal Identification from Video

    Kuncheva, L., Garrido-Labrador, J., Ramos-Perez, I., Hennessey, S. & Rodriguez, J., 1 Apr 2024, In: Information Fusion. 104, 102188.

    Research output: Contribution to journal › Article › peer-review

21. Published

    Ten measures of diversity in classifier ensembles: Limits for two classifiers.

    Kuncheva, L. I. & Whitaker, C. J., 1 Jan 2001.

    Research output: Contribution to conference › Paper

22. Published

    `Fuzzy' vs `Non-fuzzy' in combining classifiers designed by boosting.

    Kuncheva, L. I., 1 Dec 2003, In: IEEE Transactions on Fuzzy Systems. 11, 6, p. 729-741

    Research output: Contribution to journal › Article › peer-review

23. Published

    Restricted Set Classification: Who is there?, Pattern Recognition

    Kuncheva, L. I., Rodriguez, J. J. & Jackson, A. S., 1 Mar 2017, In: Pattern Recognition. 63, C, p. 158-170

    Research output: Contribution to journal › Article › peer-review

24. Published

    Limits on the majority vote accuracy in classifier fusion.

    Kuncheva, L. I., Whitaker, C. J., Shipp, C. A. & Duin, R. P., 1 Apr 2003, In: Pattern Analysis and Applications. 6, 1, p. 22-31

    Research output: Contribution to journal › Article › peer-review

25. Published

    Classifier ensembles for fMRI data analysis: an experiment.

    Kuncheva, L. I. & Rodriguez, J. J., 1 May 2010, In: Magnetic Resonance Imaging. 28, 4, p. 583-593

    Research output: Contribution to journal › Article › peer-review

26. Published

    Diversity in multiple classifier systems.

    Kuncheva, L. I., 1 Jan 2005, In: Information Fusion. 6, 1, p. 3-4

    Research output: Contribution to journal › Article › peer-review

27. Published

    On feature selection protocols for very low-sample-size data

    Kuncheva, L. & Rodriguez, J., Sept 2018, In: Pattern Recognition. 81, p. 660-673 14 p.

    Research output: Contribution to journal › Article › peer-review

28. Published

    Comparing Keyframe Summaries of Egocentric Videos: Closest-to-Centroid Baseline

    Kuncheva, L., Yousefi, P. & Almeida, J., 12 Mar 2018, In: International Conference on Image Processing Theory, Tools and Applications (IPTA).

    Research output: Contribution to journal › Conference article › peer-review

29. Published

    Classifier ensembles with a random linear oracle.

    Kuncheva, L. I. & Rodriguez, J. J., 1 Apr 2007, In: IEEE Transactions on Knowledge and Data Engineering. 19, 4, p. 500-508

    Research output: Contribution to journal › Article › peer-review

30. Published

    Pattern Recognition.

    Kuncheva, L. I., Everitt, B. S. (Editor) & Howell, D. (Editor), 1 Jan 2005, Encyclopedia of Statistics in Behavioral Science. 2005 ed. Wiley, Vol. 3. p. 1532-1535

    Research output: Chapter in Book/Report/Conference proceeding › Chapter

31. Published

    Classifier ensembles for detecting concept change in streaming data: Overview and perspectives

    Kuncheva, L. I., 1 Jan 2008, p. 5-10.

    Research output: Contribution to conference › Paper

32. Published

    On the optimality of Naive Bayes with dependent binary features.

    Kuncheva, L. I., 1 May 2006, In: Pattern Recognition Letters. 27, 7, p. 830-837

    Research output: Contribution to journal › Article › peer-review

33. Published

    An ensemble-based method for linear feature extraction for two-class problems.

    Masip, D., Kuncheva, L. I. & Vitria, J., 1 Dec 2005, In: Pattern Analysis and Applications. 8, 3, p. 227-237

    Research output: Contribution to journal › Article › peer-review

34. Published

    Using control charts for online video summarisation

    Matthews, C., Yousefi, P. & Kuncheva, L., 2018. 10 p.

    Research output: Contribution to conference › Paper › peer-review

35. Published

    Classification and Comparison of On-Line Video Summarisation Methods

    Matthews, C. E., Kuncheva, L. I. & Yousefi, P., Apr 2019, In: Machine Vision and Applications. 30, 3, p. 507-518

    Research output: Contribution to journal › Article › peer-review

36. Published

    A framework for generating data to simulate changing environments.

    Narasimhamurthy, A. & Kuncheva, L. I., 1 Jan 2007, p. 384-389.

    Research output: Contribution to conference › Paper

37. Published

    Naive random subspace ensemble with linear classifiers for real-time classification of fMRI data

    Plumpton, C. O., Kuncheva, L. I., Oosterhof, N. N. & Johnston, S. J., Jun 2012, In: Pattern Recognition. 45, 6, p. 2101-2108

    Research output: Contribution to journal › Article › peer-review

38. Published

    Learn ++.MF: A random subspace approach for the missing feature problem.

    Polikar, R., DePasquale, J., Mohammed, H. S., Brown, G. & Kuncheva, L. I., 1 Nov 2010, In: Pattern Recognition. 43, 11, p. 3817-3832

    Research output: Contribution to journal › Article › peer-review

39. Published

    Visualisation Data Modelling Graphics (VDMG) at Bangor

    Roberts, J. C., Ritsos, P. D., Kuncheva, L., Vidal, F., Lim, I. S., Ap Cenydd, L., Teahan, W., Mansoor, S., Gray, C. & Perkins, D., May 2021. 2 p.

    Research output: Contribution to conference › Paper › peer-review

40. Published

    Rotation forest: A new classifier ensemble method.

    Rodriguez, J. J. & Kuncheva, L. I., 1 Oct 2006, In: IEEE Transactions on Pattern Analysis and Machine Intelligence. 28, 10, p. 1619-1630

    Research output: Contribution to journal › Article › peer-review

41. Published

    Time series classification: Decision forests and SVM on interval and DTW features

    Rodriguez, J. J. & Kuncheva, L. I., 1 Jan 2007.

    Research output: Contribution to conference › Paper

42. Published

    Random Balance ensembles for multiclass imbalance learning

    Rodriguez, J., Diez-Pastor, J.-F., Arnaiz-Gonzalez, A. & Kuncheva, L., 6 Apr 2020, In: Knowledge-Based Systems. 193, 24 p., 105434.

    Research output: Contribution to journal › Article › peer-review

43. Published

    Naive Bayes ensembles with a random oracle.

    Rodriguez, J. J. & Kuncheva, L. I., 1 Jan 2007, p. 450-458.

    Research output: Contribution to conference › Paper

44. Published

    An Experimental Evaluation of Mixup Regression Forests

    Rodriguez, J., Juez-Gil, M., Arnaiz-Gonzalez, A. & Kuncheva, L., 1 Aug 2020, In: Expert Systems with Applications. 151, 113376.

    Research output: Contribution to journal › Article › peer-review

45. Published

    Data reduction using classifier ensembles.

    Sanchez, J. S. & Kuncheva, L. I., 1 Jan 2007.

    Research output: Contribution to conference › Paper

46. Published

    Relationships between combination methods and measures of diversity in combining classifiers

    Shipp, C. A. & Kuncheva, L. I., 1 Jan 2003, In: Information Fusion. 3, 2, p. 135-148

    Research output: Contribution to journal › Article › peer-review

47. Published

    Four measures of data complexity for bootstrapping, splitting and feature sampling

    Shipp, C. A. & Kuncheva, L. I., 1 Jan 2001, p. 429-435.

    Research output: Contribution to conference › Paper

48. Published

    An investigation into how AdaBoost affects classifier diversity.

    Shipp, C. A. & Kuncheva, L. I., 1 Jan 2002, p. 203-208.

    Research output: Contribution to conference › Paper

49. Published

    Bagging and Boosting for the nearest mean classifier: Effects of sample size on diversity and accuracy

    Skurichina, M., Kuncheva, L. I. & Duin, R. P., 1 Jan 2002, p. 62-71.

    Research output: Contribution to conference › Paper

50. Published

    ROC curves and video analysis optimization in intestinal capsule endoscopy.

    Vilarino, F., Kuncheva, L. I. & Radeva, P., 1 Jun 2006, In: Pattern Recognition Letters. 27, 8, p. 875-881

    Research output: Contribution to journal › Article › peer-review