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Dragan Gamberger: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Dragan Gamberger, Nada Lavrac, Ciril Groselj
    Diagnostic Rules of Increased Reliability for Critical Medical Applications. [Citation Graph (0, 0)][DBLP]
    AIMDM, 1999, pp:361-365 [Conf]
  2. Dragan Gamberger
    Inductively Learned Rule for Breast Cancer Domain with Improved Interobserver Reproductibility. [Citation Graph (0, 0)][DBLP]
    AIME, 1995, pp:431-432 [Conf]
  3. Dragan Gamberger, Nada Lavrac
    Analysis of Gene Expression Data by the Logic Minimization Approach. [Citation Graph (0, 0)][DBLP]
    AIME, 2003, pp:244-248 [Conf]
  4. Goran Krstacic, Dragan Gamberger, Tomislav Smuc
    Coronary Heart Disease Patient Models Based on Inductive Machine Learning. [Citation Graph (0, 0)][DBLP]
    AIME, 2001, pp:113-116 [Conf]
  5. Tomislav Smuc, Dragan Gamberger, Goran Krstacic
    Combining Unsupervised and Supervised Machine Learning. [Citation Graph (0, 0)][DBLP]
    AIME, 2001, pp:109-112 [Conf]
  6. Dragan Gamberger, Nada Lavrac, Saso Dzeroski
    Noise Elimination in Inductive Concept Learning: A Case Study in Medical Diagnosois. [Citation Graph (0, 0)][DBLP]
    ALT, 1996, pp:199-212 [Conf]
  7. Nada Lavrac, Dragan Gamberger, Peter D. Turney
    Cost-Sensitive Feature Reduction Applied to a Hybrid Genetic Algorithm. [Citation Graph (0, 0)][DBLP]
    ALT, 1996, pp:127-134 [Conf]
  8. Nada Lavrac, Dragan Gamberger
    Relevancy in Constraint-Based Subgroup Discovery. [Citation Graph (0, 0)][DBLP]
    Constraint-Based Mining and Inductive Databases, 2004, pp:243-266 [Conf]
  9. Dragan Gamberger, Nada Lavrac
    Avoiding Data Overfitting in Scientific Discovery: Experiments in Functional Genomics. [Citation Graph (0, 0)][DBLP]
    ECAI, 2004, pp:470-474 [Conf]
  10. Dragan Gamberger
    A Minimization Approach to Propositional Inductive Learning. [Citation Graph (0, 0)][DBLP]
    ECML, 1995, pp:151-160 [Conf]
  11. Dragan Gamberger, Nada Lavrac
    Conditions for Occam's Razor Applicability and Noise Elimination. [Citation Graph (0, 0)][DBLP]
    ECML, 1997, pp:108-123 [Conf]
  12. Dragan Gamberger
    High-Speed Routing Algorithms Based on Integer Residue Number Arithmetic. [Citation Graph (0, 0)][DBLP]
    ICCC, 1986, pp:637-642 [Conf]
  13. Dragan Gamberger, Nada Lavrac
    Descriptive Induction through Subgroup Discovery: A Case Study in a Medical Domain. [Citation Graph (0, 0)][DBLP]
    ICML, 2002, pp:163-170 [Conf]
  14. Dragan Gamberger, Nada Lavrac, Ciril Groselj
    Experiments with Noise Filtering in a Medical Domain. [Citation Graph (0, 0)][DBLP]
    ICML, 1999, pp:143-151 [Conf]
  15. Dragan Gamberger, Nada Lavrac
    Noise Detection and Elimination Applied to Noise Handling in a KRK Chess Endgame. [Citation Graph (0, 0)][DBLP]
    Inductive Logic Programming Workshop, 1996, pp:72-88 [Conf]
  16. Dragan Gamberger, Goran Krstacic, Tomislav Smuc
    Medical Expert Evaluation of Machine Learning Results for a Coronary Heart Disease Database. [Citation Graph (0, 0)][DBLP]
    ISMDA, 2000, pp:159-168 [Conf]
  17. Dragan Gamberger, Nada Lavrac, Goran Krstacic, Tomislav Smuc
    Inconsistency Tests for Patient Records in a Coronary Heart Disease Database. [Citation Graph (0, 0)][DBLP]
    ISMDA, 2000, pp:183-189 [Conf]
  18. Dragan Gamberger, Nada Lavrac
    Confirmation Rule Sets. [Citation Graph (0, 0)][DBLP]
    PKDD, 2000, pp:34-43 [Conf]
  19. Dragan Gamberger, Nada Lavrac
    Generating Actionable Knowledge by Expert-Guided Subgroup Discovery. [Citation Graph (0, 0)][DBLP]
    PKDD, 2002, pp:163-174 [Conf]
  20. Dragan Gamberger, Nada Lavrac, Saso Dzeroski
    Noise Detection and Elimination in data Proprocessing: Experiments in Medical Domains. [Citation Graph (0, 0)][DBLP]
    Applied Artificial Intelligence, 2000, v:14, n:2, pp:205-223 [Journal]
  21. Dragan Gamberger, Nada Lavrac
    Active subgroup mining: a case study in coronary heart disease risk group detection. [Citation Graph (0, 0)][DBLP]
    Artificial Intelligence in Medicine, 2003, v:28, n:1, pp:27-57 [Journal]
  22. Nada Lavrac, Dragan Gamberger, Peter D. Turney
    A Relevancy Filter for Constructive Induction. [Citation Graph (0, 0)][DBLP]
    IEEE Intelligent Systems, 1998, v:13, n:2, pp:50-56 [Journal]
  23. Dragan Gamberger, Sanja Sekusak, Aleksandar Sabljic
    Modelling Biodegradation by an Example-Based Learning System. [Citation Graph (0, 0)][DBLP]
    Informatica (Slovenia), 1993, v:17, n:2, pp:- [Journal]
  24. Dragan Gamberger, Nada Lavrac
    Expert-Guided Subgroup Discovery: Methodology and Application. [Citation Graph (0, 0)][DBLP]
    J. Artif. Intell. Res. (JAIR), 2002, v:17, n:, pp:501-527 [Journal]
  25. Dragan Gamberger, Nada Lavrac, Filip Zelezný, Jakub Tolar
    Induction of comprehensible models for gene expression datasets by subgroup discovery methodology. [Citation Graph (0, 0)][DBLP]
    Journal of Biomedical Informatics, 2004, v:37, n:4, pp:269-284 [Journal]
  26. Dragan Gamberger, Nada Lavrac, Goran Krstacic
    Confirmation rule induction and its applications to coronary heart disease diagnosis and risk group discovery. [Citation Graph (0, 0)][DBLP]
    Journal of Intelligent and Fuzzy Systems, 2002, v:12, n:1, pp:35-48 [Journal]
  27. Nada Lavrac, Dragan Gamberger, Viktor Jovanoski
    A Study of Relevance for Learning in Deductive Databases. [Citation Graph (0, 0)][DBLP]
    J. Log. Program., 1999, v:40, n:2-3, pp:215-249 [Journal]
  28. Nada Lavrac, Bojan Cestnik, Dragan Gamberger, Peter A. Flach
    Decision Support Through Subgroup Discovery: Three Case Studies and the Lessons Learned. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2004, v:57, n:1-2, pp:115-143 [Journal]
  29. Dragan Gamberger, Nada Lavrac
    Supporting Factors in Descriptive Analysis of Brain Ischaemia. [Citation Graph (0, 0)][DBLP]
    AIME, 2007, pp:155-159 [Conf]
  30. Petra Kralj, Nada Lavrac, Dragan Gamberger, Antonija Krstacic
    Contrast Set Mining for Distinguishing Between Similar Diseases. [Citation Graph (0, 0)][DBLP]
    AIME, 2007, pp:109-118 [Conf]
  31. Petra Kralj, Nada Lavrac, Dragan Gamberger, Antonija Krstacic
    Contrast Set Mining Through Subgroup Discovery Applied to Brain Ischaemina Data. [Citation Graph (0, 0)][DBLP]
    PAKDD, 2007, pp:579-586 [Conf]

  32. Advances in Class Noise Detection. [Citation Graph (, )][DBLP]


  33. Handling Unknown and Imprecise Attribute Values in Propositional Rule Learning: A Feature-Based Approach. [Citation Graph (, )][DBLP]


  34. Medical Knowledge Representation within Heartfaid Platform. [Citation Graph (, )][DBLP]


  35. Semantic Web Ontology Utilization for Heart Failure Expert System Design. [Citation Graph (, )][DBLP]


  36. Clinical data analysis based on iterative subgroup discovery: experiments in brain ischaemia data analysis. [Citation Graph (, )][DBLP]


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