| 2007 |
| 0506 | M. Drobics, J. Himmelbauer. Creating comprehensible regression models. Soft Computing - A Fusion of Foundations, Methodologies and Applications, volume 11, number 5, pages 421-438, 2007. |
| 2005 |
| 0507 | M. Drobics. FS-LiRT - An inductive learning method for creating comprehensible fuzzy regression trees. Technical Report, SCCH-TR-0507, SCCH, 2005. |
| 0509 | M. Drobics. Inductive learning of fuzzy regression trees. Proc. 4th Conf. of the European Society for Fuzzy Logic and Technology and 11 Recontres Francophones sur al Logique Flou et ses Applications (EUSFLAT/LFA 2005), pages 16-21, 2005. |
| 0515 | M. Drobics. Data analysis using fuzzy expressions - creating comprehensible computational models from data. PhD thesis, 2005. |
| 0517 | M. Drobics, J. Botzheim. A bacterial evolutionary algorithm for feature selection. Technical Report, SCCH-TR-0517, SCCH, 2005. |
| 0531 | T. Natschläger, M. Drobics, F. Kossak. machine learning framework for Mathematica V1.3: Creating interpretable computational models from data. Proc. Wolfram Technology Conf., pages online, 2005. |
| 2004 |
| 0408 | J. Botzheim, M. Drobics, L. Kóczy. Feature selection using bacterial optimization. Proc. 10th Int. Conf. on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2004), pages 797-804, 2004. |
| 0404 | M. Drobics. Choosing the best predicates for data-driven fuzzy modeling. Proc. 13th IEEE Int. Conf. on Fuzzy Systems, pages 245 - 249, IEEE Press. 2004. |
| 0427 | M. Drobics, U. Bodenhofer, M. Mittendorfer. A three-stage approach to descriptive data analysis - Identifying clusters and corresponding interpretable descriptions from large data sets. Proc. 7th COST Action 276 Workshop, 2004. |
| 0425 | M. Drobics, F. Kossak, T. Natschläger. machine learning framework for Mathematica V1.2 - Creating interpretable computational models from data. Proc. Mathematica Technology Conf., pages online, 2004. |
| 0405 | J. Himmelbauer, M. Drobics. Regularized numerical optimization of fuzzy rule bases. Proc. 13th IEEE Int. Conf. on Fuzzy Systems, pages 1655 - 1660, IEEE Press. 2004. |
| 0403 | T. Natschläger, F. Kossak, M. Drobics. Extracting knowledge and computable models from data - Needs, expectations, and experience. Proc. 13th IEEE Int. Conf. on Fuzzy Systems, pages 493 - 498, IEEE Press. 2004. |
| 2003 |
| 0325 | M. Drobics. Machine learning framework for Mathematica - Creating understandable computational models from data. Proc. Mathematica Developer Conf. 2003, pages online, 2003. |
| 0201 | M. Drobics, U. Bodenhofer, E. Klement. FS-FOIL: An inductive learning method for extracting interpretable fuzzy descriptions. International Journal of Approximate Reasoning, volume 32, number 2-3, pages 131-152, 2003. |
| 0317 | M. Drobics, J. Botzheim. Feature selection using bacterial optimization. Technical Report, SCCH-TR-0317, SCCH, 2003. |
| 2002 |
| 0206 | M. Drobics. Fuzzy decision trees - induction and deduction. Technical Report, SCCH-TR-0206, SCCH, 2002. |
| 0238 | M. Drobics, U. Bodenhofer. Fuzzy modeling with decision trees. Proc. 2002 IEEE Int. Conf. on Systems, Man, and Cybernetics (IEEE SMC'02), IEEE Computer Society. 2002. |
| 0123 | M. Drobics, U. Bodenhofer, W. Winiwarter. Mining clusters and corresponding interpretable descriptions - A three-stage approach. Expert Systems: The Journal of Knowledge Engineering and Neural Networks, volume 19, number 4, pages 224-234, 2002. |
| 0249 | P. Hobelsberger, M. Drobics, R. Wegenkittl. Analysis and visualization of 4D medical images using self-organizing maps and clustering.
In F. Leberl, F. Frauendorfer (editors).
Vision with Non-Traditional Sensors - Proc. 26th Workshop of the Austrian Association for Pattern Recognition (ÖAGM/AAPR), pages 273-280, OCG. 2002. |
| 2001 |
| 0106 | M. Drobics. Image segmentation and labeling using SOMs. Technical Report, SCCH-TR-0106, SCCH, 2001. |
| 0114 | M. Drobics, U. Bodenhofer, W. Winiwarter, E. Klement. Data mining using synergies between self-organizing maps and inductive learning of fuzzy rules. Proc. Joint 9th IFSA World Congress and 20th NAFIPS Int. Conf. (IFSA-NAFIPS 2001), pages 1780-1785, 2001. |
| 2000 |
| 0008 | M. Drobics. Finding fuzzy descriptions using SOMs. Technical Report, SCCH-TR-0008, SCCH, 2000. |
| 0071 | M. Drobics. Advanced fuzzy clustering. Technical Report, SCCH-TR-0071, SCCH, 2000. |
| 0016 | M. Drobics, W. Winiwarter, U. Bodenhofer. Interpretation of self-organizing maps with fuzzy rules. Proc. 12th IEEE Int.l Conf. on Tools with Artificial Intelligence (ICTAI 2000), pages 304-311, 2000. |