Ludmila I Kuncheva

Summary

Country: UK

Publications

  1. ncbi request reprint Evaluation of stability of k-means cluster ensembles with respect to random initialization
    Ludmila I Kuncheva
    School of Informatics, University of Wales, Bangor, Gwynedd, UK
    IEEE Trans Pattern Anal Mach Intell 28:1798-808. 2006
  2. ncbi request reprint Diagnosing scrapie in sheep: a classification experiment
    Ludmila I Kuncheva
    School of Informatics, University of Wales, Bangor, UK
    Comput Biol Med 37:1194-202. 2007
  3. doi request reprint Error-dependency relationships for the naïve Bayes classifier with binary features
    Ludmila I Kuncheva
    School of Computer Science, Bangor University, Sean Street, Bangor, Gwynedd, UK
    IEEE Trans Pattern Anal Mach Intell 30:735-40. 2008
  4. doi request reprint Random subspace ensembles for FMRI classification
    Ludmila I Kuncheva
    School of Computer Science, Bangor University, LL57 1UT Bangor, U K
    IEEE Trans Med Imaging 29:531-42. 2010
  5. doi request reprint Classifier ensembles for fMRI data analysis: an experiment
    Ludmila I Kuncheva
    School of Computer Science, Bangor University, LL57 1UT, UK
    Magn Reson Imaging 28:583-93. 2010
  6. ncbi request reprint Rotation forest: A new classifier ensemble method
    Juan J Rodriguez
    Escuela Politecnica Superior, Edificio C, Universidad de Burgos, c Francisco de Vitoria s n, 09006 Burgos, Spain
    IEEE Trans Pattern Anal Mach Intell 28:1619-30. 2006

Detail Information

Publications6

  1. ncbi request reprint Evaluation of stability of k-means cluster ensembles with respect to random initialization
    Ludmila I Kuncheva
    School of Informatics, University of Wales, Bangor, Gwynedd, UK
    IEEE Trans Pattern Anal Mach Intell 28:1798-808. 2006
    ..Following the hypothesis that a point of stability of a clustering algorithm corresponds to a structure found in the data, we used the stability measures to pick the number of clusters. The combined stability index gave best results...
  2. ncbi request reprint Diagnosing scrapie in sheep: a classification experiment
    Ludmila I Kuncheva
    School of Informatics, University of Wales, Bangor, UK
    Comput Biol Med 37:1194-202. 2007
    ..The results suggest that the clinical classification by the VO was adequate as no further differentiation within the set of suspects was feasible...
  3. doi request reprint Error-dependency relationships for the naïve Bayes classifier with binary features
    Ludmila I Kuncheva
    School of Computer Science, Bangor University, Sean Street, Bangor, Gwynedd, UK
    IEEE Trans Pattern Anal Mach Intell 30:735-40. 2008
    ..A measure of discrepancy of feature dependencies is proposed for multiple features. Its correlation with NB is shown using 23 real data sets...
  4. doi request reprint Random subspace ensembles for FMRI classification
    Ludmila I Kuncheva
    School of Computer Science, Bangor University, LL57 1UT Bangor, U K
    IEEE Trans Med Imaging 29:531-42. 2010
    ..The closest rivals were the single SVM and bagging of SVM classifiers. We use kappa-error diagrams to understand the success of RS...
  5. doi request reprint Classifier ensembles for fMRI data analysis: an experiment
    Ludmila I Kuncheva
    School of Computer Science, Bangor University, LL57 1UT, UK
    Magn Reson Imaging 28:583-93. 2010
    ..The best classifiers were found to be the random subspace ensemble of SVM classifiers, rotation forest and ensembles with random linear and random spherical oracle...
  6. ncbi request reprint Rotation forest: A new classifier ensemble method
    Juan J Rodriguez
    Escuela Politecnica Superior, Edificio C, Universidad de Burgos, c Francisco de Vitoria s n, 09006 Burgos, Spain
    IEEE Trans Pattern Anal Mach Intell 28:1619-30. 2006
    ..Diversity-error diagrams revealed that Rotation Forest ensembles construct individual classifiers which are more accurate than these in AdaBoost and Random Forest, and more diverse than these in Bagging, sometimes more accurate as well...